Frameworks Support Matrix :: NVIDIA Deep Learning Frameworks Documentation

Abstract

This support matrix is for NVIDIA optimized frameworks. The matrix provides a single view into the supported software and specific versions that come packaged with the frameworks based on the container image.

1. 22.xx Framework Containers Support Matrix

Important: Content that is included in <<>> brackets indicates new content from the previously published version.

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 22.01 release of an image was released in January 2022.

22.xx container images

Table 1. Software stack packaged with the 22.xx container images
Container Image	22.02		22.01
DGX
DGX System	DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100
Operating System	DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0+ Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 5.1 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹
System Requirements
NVIDIA Driver	Release 22.02 is based on NVIDIA CUDA 11.6.0, which requires NVIDIA Driver release 510 or later. However, if you are running on a Data Center GPU (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), 460.27 (or later R460), or 470.57 (or later R470). The CUDA driver's compatibility package only supports particular drivers. ³		Release 22.01 is based on NVIDIA CUDA 11.6.0, which requires NVIDIA Driver release 510 or later. However, if you are running on a Data Center GPU (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), 460.27 (or later R460), or 470.57 (or later R470). The CUDA driver's compatibility package only supports particular drivers. ³
GPU Model	NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal
Base Container Image (included in all containers)
Container OS	Ubuntu 20.04		Ubuntu 20.04
CUDA	NVIDIA CUDA 11.6.0		NVIDIA CUDA 11.6.0
cuBLAS	11.8.1.74		11.8.1.74
cuDNN	8.3.2.44		8.3.2.44
cuTENSOR	1.4		1.4
DALI	<<1.10.0>>		1.9.0
NCCL	2.11.4		2.11.4
TensorRT	<<TensorRT 8.2.3>>		TensorRT 8.2.2
rdma-core	36.0		36.0
NVIDIA HPC-X	2.10 with OpenMPI 4.1.2rc4+ OpenUCX 1.12.0		2.10 with OpenMPI 4.1.2rc4+ OpenUCX 1.12.0
GDRcopy	2.3		2.3
Nsight Systems	2021.5.2.53		2021.5.2.53
NVIDIA Optimized Frameworks
Kaldi	26b9f648 Python 3.8		26b9f648 Python 3.8
Kaldi	Docker image size: 9 GB		Docker image size: 8.96 GB
PyTorch	<<1.11.0a0+17540c5c>> including Python 3.8 APEX Nsight Compute 2022.1.0.0 TensorBoard 2.8.0 Torch-TensorRT 1.1.0a0 MAGMA 2.5.2 RAPIDS 21.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.11.0a0+bfe5ad28 including Python 3.8 APEX Nsight Compute 2022.1.0.0 TensorBoard 2.8.0 Torch-TensorRT 1.1.0a0 MAGMA 2.5.2 RAPIDS 21.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard
PyTorch	Docker image size: 14.4 GB		Docker image size: 14.8 GB
TensorFlow	2.7.0 including Python 3.8 Horovod 0.23.0 TensorBoard 2.7.0 RAPIDS 21.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 <<JupyterLab 2.3.2>> JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `22.02-tf1-py3`contains Python 3.8 Horovod 0.23.0 TensorBoard 1.15.0 <<Nsight Compute 2022.1.0.2>> RAPIDS 21.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 <<JupyterLab 2.3.2>> JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.7.0 including Python 3.8 Horovod 0.23.0 TensorBoard 2.7.0 RAPIDS 21.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `22.01-tf1-py3`contains Python 3.8 Horovod 0.23.0 TensorBoard 1.15.0 Nsight Compute 2021.3.0.13 RAPIDS 21.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard
TensorFlow	Docker image size: 13.1 GB	Docker image size: 14.5 GB	Docker image size: 13.1 GB	Docker image size: 15.1 GB
TensorRT	TensorRT 8.2.2 including: Python 3.8		TensorRT 8.2.2 including: Python 3.8
TensorRT	Docker image size: 6.21 GB		Docker image size: 6.17 GB
Triton Inference Server	In addition to the hardware and software listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU <<2.19.0>> including <<1.11.0a0+17540c5c>> TensorFlow 1.15.5 TensorFlow 2.7.0 ONNX Runtime 1.9.0 Intel OpenVINO 2021.2 DCGM 2.2.9 FIL		In addition to the hardware and software listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.18.0 including PyTorch 1.11.0a0+bfe5ad2 TensorFlow 1.15.5 TensorFlow 2.7.0 ONNX Runtime 1.9.0 Intel OpenVINO 2021.2 DCGM 2.2.9 FIL
Triton Inference Server	Docker image size: 12.3 GB		Docker image size: 12.4 GB
TensorFlow For Jetson	TensorFlow 1.15.5 and 2.7.0 for Jetson		TensorFlow 1.15.5 and 2.7.0 for Jetson
Triton for Jetson	<<Triton Inference Server 2.19.0 for Jetson>> AGX Xavier Nano TX2		Triton Inference Server 2.18.0 for Jetson AGX Xavier Nano TX2

2. 21.xx Framework Containers Support Matrix

Important: Content that is included in <<>> brackets indicates new content from the previously published version.

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 21.02 release of an image was released in February 2021.

21.xx container images

Table 2. Software stack packaged with the 21.xx container images
Container Image	21.12		21.11		21.10		21.09		21.08		21.07		21.06		21.05		21.04		21.03		21.02
DGX
DGX System	DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100		DGX-1 DGX-2 DGX A100 DGX Station DGX Station A100
Operating System	DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 5.1 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 5.1 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 5.1 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 5.1 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹(4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹ Red Hat Enterprise Linux 8 / CentOS 8² (All DGX systems except DGX Station A100) EL8-20.11+¹
NVIDIA Driver	Release 21.12 is based on NVIDIA CUDA 11.5.0, which requires NVIDIA Driver release 495 or later. However, if you are running on a Data Center GPU (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), 460.27 (or later R460), or 470.57 (or later R470). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.11 is based on NVIDIA CUDA 11.5.0, which requires NVIDIA Driver release 495 or later. However, if you are running on a Data Center GPU (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), 460.27 (or later R460), or 470.57 (or later R470). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.10 is based on NVIDIA CUDA 11.4.2 with cuBLAS 11.6.5.2, which requires NVIDIA Driver release 470 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), or 460.27 (or later R460). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.09 is based on NVIDIA CUDA 11.4.2, which requires NVIDIA Driver release 470 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), or 460.27 (or later R460). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.08 is based on NVIDIA CUDA 11.4.1, which requires NVIDIA Driver release 470 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), or 460.27 (or later R460). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.07 is based on NVIDIA CUDA 11.4.0, which requires NVIDIA Driver release 470 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), or 460.27 (or later R460). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.06 is based on NVIDIA CUDA 11.3.1, which requires NVIDIA Driver release 465.19.01 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), or 460.27 (or later R460). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.05 is based on NVIDIA CUDA 11.3.0, which requires NVIDIA Driver release 465.19.01 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), or 460.27 (or later R460). The CUDA driver's compatibility package only supports particular drivers.³		Release 21.04 is based on NVIDIA CUDA 11.3.0, which requires NVIDIA Driver release 465.19.01 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51 (or later R450), or 460.27 (or later R460). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.03 is based on NVIDIA CUDA 11.2.1, which requires NVIDIA Driver release 460.32.03 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51(or later R450). The CUDA driver's compatibility package only supports particular drivers. ³		Release 21.02 is based on NVIDIA CUDA 11.2.0, which requires NVIDIA Driver release 460.27.04 or later. However, if you are running on Data Center GPUs (formerly Tesla), for example, T4, you may use NVIDIA driver release 418.40 (or later R418), 440.33 (or later R440), 450.51(or later R450). The CUDA driver's compatibility package only supports particular drivers.³
GPU Model	NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal
Base Container Image
Container OS	Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04		Ubuntu 20.04
CUDA	NVIDIA CUDA 11.5.0		NVIDIA CUDA 11.5.0		NVIDIA CUDA 11.4.2 with cuBLAS 11.6.5.2		11.4.2		11.4.1		11.4.0		11.3.1		11.3.0		11.3.0		11.2.1		11.2.0
cuBLAS	11.7.3.1		11.7.3.1		11.6.1.51		11.6.1.51		11.5.4		11.5.2.43		11.5.1.109		11.5.1.101		11.5.1.101		11.4.1.1026		11.3.1.68
cuDNN	8.3.1.22		8.3.0.96		8.2.4.15		8.2.4.15		8.2.2.26		8.2.2.26		8.2.1		8.2.0.51		8.2.0.41		8.1.1		8.1.0.77
NCCL	2.11.4		2.11.4		2.11.4		2.11.4		2.10.3		2.10.3		2.9.9		2.9.8		2.9.6		2.8.4		2.8.4
TensorRT	TensorRT 8.2.1.8		TensorRT 8.0.3.4		TensorRT 8.0.3.4
NVIDIA Optimized Frameworks
Kaldi	c6772ba4 Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4		c6772ba4 Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4		2897564e Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4		40573bb Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.1.57 TensorRT 8.0.3		851a0a79 Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.2 NVIDIA HPC-X 2.9 Nsight Systems 2021.2.4.12 TensorRT 8.0.1.6		9bca2777 Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.4.12 TensorRT 8.0.1.6		b1786aa5 Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.1.58 TensorRT 7.2.3.4		e92970ae Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 TensorRT 7.2.3.4		ec554a7c Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 TensorRT 7.2.3.4		376281ca Python 3.8 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 TensorRT 7.2.2.3		b78fdcaf Python 3.8 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 TensorRT 7.2.2.3+cuda11.1.0.024
Kaldi	Docker image size: 8.78 GB		Docker image size: 8.69 GB		Docker image size: 9.16 GB		Docker image size: 9.12 GB		Docker image size: 8.86 GB		Docker image size: 8.77 GB		Docker image size: 8.62 GB		Docker image size: 8.43 GB		Docker image size: 8.3 GB		Docker image size: 8.62 GB		Docker image size: 8.73 GB
DIGITS	Release paused		Release paused		Release paused		6.1.1 including Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.1.57 TensorFlow 1.15.5 TensorRT 8.0.3		6.1.1 including Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.2 NVIDIA HPC-X 2.9 Nsight Systems 2021.2.4.12 TensorFlow 1.15.5 TensorRT 8.0.1.6		6.1.1 including Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.4.12 TensorFlow 1.15.5 TensorRT 8.0.1.6		6.1.1 including Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.1.58 TensorFlow 1.15.5 TensorRT 7.2.3.4		6.1.1 including Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 TensorFlow 1.15.5 TensorRT 7.2.3.4		6.1.1 including Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 TensorFlow 1.15.5 TensorRT 7.2.3.4		6.1.1 including Python 3.8 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 TensorFlow 1.15.5 TensorRT 7.2.2.3		6.1.1 including Python 3.8 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 TensorFlow 1.15.5 TensorRT 7.2.2.3+cuda11.1.0.024
DIGITS	-		-		-		Docker image size: 14.6 GB		Docker image size: 14.9 GB		Docker image size: 15 GB		Docker image size: 14.7 GB		Docker image size: 15.1 GB		Docker image size: 15.1 GB		Docker image size: 15.4 GB		Docker image size: 15.5 GB
NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet	Release paused		Release paused		Release paused		1.9.0.rc6 including Sockeye 2.2.3 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Compute 2021.2.2.0 Nsight Systems 2021.3.1.57 Horovod 0.22.1 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 8.0.3 DALI 1.5.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.2.9 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.9.0.rc6 including Sockeye 2.2.3 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.2 NVIDIA HPC-X 2.9 Nsight Systems 2021.2.4.12 Horovod 0.22.1 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 8.0.1.6 DALI 1.4.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.2.9 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.9.0.rc3 including Sockeye 2.2.3 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.4.12 Horovod 0.22.1 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 8.0.1.6 DALI 1.3.0 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.2.9 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.9.0.rc2 including Sockeye 2.2.3 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.1.58 Horovod 0.21.3 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.3.4 DALI 1.2.0 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.8.0 including Sockeye 2.2.3 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.4.3.7 Horovod 0.21.3 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.3.4 DALI 1.0.0 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.8.0 including Sockeye 2.2.3 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.4.3.7 Horovod 0.21.3 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.3.4 DALI 1.0.0 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.8.0 including Sockeye 2.2.3 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Horovod 0.21.2 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.2.3 DALI 0.31 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.8.0.rc2 including Sockeye 2.2.3 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Horovod 0.21.0 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.2.3+cuda11.1.0.024 DALI 0.29 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard
	-		-		-		Docker image size: 11.2 GB		Docker image size: 10.9 GB		Docker image size: 10.6 GB		Docker image size: 10.4 GB		Docker image size: 10.8 GB		Docker image size: 10.7 GB		Docker image size: 11.1 GB		Docker image size: 10.8 GB
PyTorch	1.11.0a0+b6df043 including Python 3.8 APEX rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 TensorRT 8.2.1.8 Nsight Compute 2021.3.0.13 Nsight Systems 2021.3.2.4 TensorBoard 2.7.0 Torch-TensorRT 1.1.0a0 DALI 1.8 MAGMA 2.5.2 DLProf 1.8.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.11.0a0+b6df043 including Python 3.8 APEX rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux Nsight Compute 2021.3.0.13 Nsight Systems 2021.3.2.4 TensorBoard 2.7.0 Torch-TensorRT 1.0.0a0 DALI 1.7 MAGMA 2.5.2 DLProf 1.7.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.10.0a0+0aef44c including Python 3.8 APEX rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux Nsight Systems 2021.3.1.57 TensorBoard 2.6.0 DALI 1.6 MAGMA 2.5.2 DLProf 1.6.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.10.0a0+3fd9dcf including Python 3.8 APEX rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.1.57 TensorBoard 2.6.0 DALI 1.5 MAGMA 2.5.2 DLProf 1.5.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.10.0a0+3fd9dcf including Python 3.8 APEX rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.2 NVIDIA HPC-X 2.9 Nsight Systems 2021.2.4.12 TensorBoard 2.6.0 TensorRT 8.0.1.6 DALI 1.4 MAGMA 2.5.2 DLProf 1.4.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.10.0a0+ecc3718 including Python 3.8 APEX rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.2.0 Nsight Systems 2021.2.4.12 TensorBoard 2.5.0 TensorRT 8.0.1.6 DALI 1.3 MAGMA 2.5.2 DLProf 1.3.0 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.9.0a0+c3d40fd including Python 3.8 APEX rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.1.58 TensorBoard 1.15 TensorRT 7.2.3.4 DALI 1.2 MAGMA 2.5.2 DLProf 1.2.0 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.9.0a0+2ecb2c7 including Python 3.8 APEX rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 TensorBoard 1.15+nv TensorRT 7.2.3.4 DALI 1.0 MAGMA 2.5.2 DLProf 1.1.0 PyProf 3.10 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.9.0a0+2ecb2c7 including Python 3.8 APEX rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 TensorBoard 1.15+nv TensorRT 7.2.3.4 DALI 1.0 MAGMA 2.5.2 DLProf 1.1.0 PyProf 3.10 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.9.0a0+df837d0 including Python 3.8 APEX MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.1.0 Nsight Systems 2020.4.3.7 TensorBoard 1.15+nv TensorRT 7.2.2.3 DALI 0.31 MAGMA 2.5.2 DLProf 1.0.0 PyProf r21.03 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.8.0a0+52ea372 including Python 3.8 APEX MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 TensorBoard 1.15+nv TensorRT 7.2.2.3+cuda11.1.0.024 DALI 0.29 MAGMA 2.5.2 DLProf 0.19.0 PyProf r21.02 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b
PyTorch	Docker image size: 14.7 GB		Docker image size: 14.5 GB		Docker image size: 13.2 GB		Docker image size: 13.1 GB		Docker image size: 12.7 GB		Docker image size: 15 GB		Docker image size: 14.5 GB		Docker image size: 14.5 GB		Docker image size: 14.3 GB		Docker image size: 14.4 GB		Docker image size: 12.9 GB
TensorFlow	2.6.2 including Python 3.8 Horovod 0.22.1 TensorRT 8.2.1.8 TensorBoard 2.6.0 DALI 1.8 DLProf 1.8.0 rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 RAPIDS 21.10 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.12-tf1-py3`contains Python 3.8 Horovod 0.22.1 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 TensorRT 8.2.1.8 TensorBoard 1.15.0 RAPIDS 21.10 rdma-core 36.0 DALI 1.8 DLProf 1.8.0 Nsight Compute 2021.3.0.13 Nsight Systems 2021.3.2.4 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.6.0 including Python 3.8 Horovod 0.22.1 TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux TensorBoard 2.6.0 DALI 1.7 DLProf 1.7.0 rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.11-tf1-py3`contains Python 3.8 Horovod 0.22.1 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux TensorBoard 1.15.0 rdma-core 36.0 DALI 1.7 DLProf 1.7.0 Nsight Compute 2021.3.0.13 Nsight Systems 2021.3.2.4 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.6.0 including Python 3.8 Horovod 0.22.1 TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux TensorBoard 2.6.0 DALI 1.6 DLProf 1.6.0 rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.10-tf1-py3`contains Python 3.8 Horovod 0.22.1 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux TensorBoard 1.15.0 rdma-core 36.0 DALI 1.6 DLProf 1.6.0 Nsight Compute 2021.2.2.1 Nsight Systems 2021.3.2.4 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.6.0 including Python 3.8 Horovod 0.22.1 TensorBoard 2.6.0 TensorRT 8.0.3 DALI 1.5 DLProf 1.5.0 rdma-core 36.0 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.1.57 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.09-tf1-py3`contains Python 3.8 Horovod 0.22.1 OpenMPI 4.1.2a1 OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 TensorBoard 1.15.0 rdma-core 36.0 TensorRT 8.0.3 DALI 1.5 DLProf 1.5.0 Nsight Compute 2021.2.2.1 Nsight Systems 2021.3.1.57 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.5.0 including Python 3.8 Horovod 0.22.1 TensorBoard 2.6.0 TensorRT 8.0.1.6 DALI 1.4 DLProf 1.4.0 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.2 NVIDIA HPC-X 2.9 Nsight Systems 2021.2.4.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.08-tf1-py3`contains Python 3.8 Horovod 0.22.1 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.2 NVIDIA HPC-X 2.9 TensorBoard 1.15.0 rdma-core 36.0 OpenSeq2Seq at commit a81babd TensorRT 8.0.1.6 DALI 1.4 DLProf 1.4.0 Nsight Systems 2021.2.4.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.5.0 including Python 3.8 Horovod 0.22.1 TensorBoard 2.5.0 TensorRT 8.0.1.6 DALI 1.3 DLProf 1.3.0 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.4.12 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.07-tf1-py3`contains Python 3.8 Horovod 0.22.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 TensorBoard 1.15.0 rdma-core 32.1 OpenSeq2Seq at commit a81babd TensorRT 8.0.1.6 DALI 1.3 DLProf 1.3.0 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.4.12 Tensor Core optimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.5.0 including Python 3.8 Horovod 0.22.0 TensorBoard 2.5.0 TensorRT 7.2.3.4 DALI 1.2 DLProf 1.2.0 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.1.58 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.06-tf1-py3`contains Python 3.8 Horovod 0.22.0 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 TensorBoard 1.15.0 rdma-core 32.1 OpenSeq2Seq at commit a81babd TensorRT 7.2.3.4 DALI 1.2 DLProf 1.2.0 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.1.58 Tensor Core optimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.4.0 including Python 3.8 Horovod 0.21.3 TensorBoard 2.4.1 TensorRT 7.2.3.4 DALI 1.0 DLProf 1.1.0 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.4.3.7 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.05-tf1-py3`contains Python 3.8 Horovod 0.21.3 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 TensorBoard 1.15.0+nv21.4 rdma-core 32.1 OpenSeq2Seq at commit a81babd TensorRT 7.2.3.4 DALI 1.0 DLProf 1.1.0 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 Tensor Core optimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.4.0 including Python 3.8 Horovod 0.21.3 TensorBoard 2.4.1 TensorRT 7.2.3.4 DALI 1.0 DLProf 1.1.0 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.4.3.7 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 2.3.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.04-tf1-py3`contains Python 3.8 Horovod 0.21.3 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 TensorBoard 1.15.0+nv21.4 rdma-core 32.1 OpenSeq2Seq at commit a81babd TensorRT 7.2.3.4 DALI 1.0 DLProf 1.1.0 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7 Tensor Core optimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 2.3.1 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.4.0 including Python 3.8 Horovod 0.21.3 OpenMPI 4.0.5 TensorBoard 2.4.1 MLNX_OFED 5.1-2.3.7 TensorRT 7.2.2.3 DALI 0.31 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.03-tf1-py3`contains Python 3.8 Horovod 0.21.3 OpenMPI 4.0.5 TensorBoard 1.15.0+nv21.03 MLNX_OFED 5.1-2.3.7 OpenSeq2Seq at commit a81babd TensorRT 7.2.2.3+cuda11.1.0.024 DALI 0.31 DLProf 1.0.0 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 Tensor Core optimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.4.0 including Python 3.8 Horovod 0.21.0 OpenMPI 4.0.5 TensorBoard 2.4.1 MLNX_OFED 5.1-2.3.7 TensorRT 7.2.2.3+cuda11.1.0.024 DALI 0.29 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.5 including `21.02-tf1-py3`contains Python 3.8 Horovod 0.21.0 OpenMPI 4.0.5 TensorBoard 1.15.0+nv20.11 MLNX_OFED 5.1-2.3.7 OpenSeq2Seq at commit a81babd TensorRT 7.2.2.3+cuda11.1.0.024 DALI 0.29 DLProf 0.19.0 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7 Tensor Core optimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard
TensorFlow	Docker image size: 12.8 GB	Docker image size: 16.9 GB	Docker image size: 12.5 GB	Docker image size: 16.5 GB	Docker image size: 10.6 GB	Docker image size: 14.5 GB	Docker image size: 11.5 GB	Docker image size: 13.6 GB	Docker image size: 11.5 GB	Docker image size: 13.9 GB	Docker image size: 11.1 GB	Docker image size: 14 GB	Docker image size: 10.8 GB	Docker image size: 13.7 GB	Docker image size: 10.8 GB	Docker image size: 14.1 GB	Docker image size: 10.6 GB	Docker image size: 14.1 GB	Docker image size: 10.9 GB	Docker image size: 14.4 GB	Docker image size: 11.1 GB	Docker image size: 14.5 GB
TensorRT	TensorRT 8.2.1.8 including: Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4		TensorRT 8.0.3.4 including: Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4		TensorRT 8.0.3.4 including: Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.2.4		TensorRT 8.0.3 including: Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.3 NVIDIA HPC-X 2.9 Nsight Systems 2021.3.1.57		TensorRT 8.0.1.6 including: Python 3.8 rdma-core 36.0 OpenMPI 4.1.1+ OpenUCX 1.11.0rc1 GDRCopy 2.2 NVIDIA HPC-X 2.9 Nsight Systems 2021.2.4.12		TensorRT 8.0.1.6 including: Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.2.0 Nsight Systems 2021.2.4.12		TensorRT 7.2.3.4 including: Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.1 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2021.2.1.58		TensorRT 7.2.3.4 including: Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7		TensorRT 7.2.3.4 including: Python 3.8 rdma-core 32.1 OpenMPI 4.1.1rc1 OpenUCX 1.10.0 GDRCopy 2.2 NVIDIA HPC-X 2.8.2rc3 Nsight Compute 2021.1.3.14 Nsight Systems 2020.4.3.7		TensorRT 7.2.2.3 including: Python 3.8 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7		TensorRT 7.2.2.3+cuda11.1.0.024 including: Python 3.8 MLNX_OFED 5.1-2.3.7 OpenMPI 4.0.5 Nsight Compute 2020.3.0.18 Nsight Systems 2020.4.3.7
TensorRT	Docker image size: 5.98 GB		Docker image size: 5.88 GB		Docker image size: 6.37 GB		Docker image size: 6.3 GB		Docker image size: 6.04 GB		Docker image size: 5.95 GB		Docker image size: 5.8 GB		Docker image size: 5.76 GB		Docker image size: 5.63 GB		Docker image size: 5.94 GB		Docker image size: 7.09 GB
Triton Inference Server	In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.17.0 including TensorRT 8.2.1.8 PyTorch 1.11.0a0+b6df043 TensorFlow 1.15.5 TensorFlow 2.6.2 ONNX Runtime 1.9.0 Intel OpenVINO 2021.2 DCGM 2.2.9 FIL DALI 1.8		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.16.0 including TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux PyTorch 1.11.0a0+b6df043 TensorFlow 1.15.5 TensorFlow 2.6.0 ONNX Runtime 1.9.0 Intel OpenVINO 2021.2 DCGM 2.2.9 FIL DALI 1.7		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.15.0 including TensorRT 8.0.3.4 for x64 Linux TensorRT 8.0.2.2 for ARM SBSA Linux PyTorch 1.10.0a0+0aef44c TensorFlow 1.15.5 TensorFlow 2.6.0 ONNX Runtime 1.9.0 Intel OpenVINO 2021.2 DCGM 2.2.9 FIL DALI 1.6		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.14.0 including TensorRT 8.0.3 PyTorch 1.10.0a0+3fd9dcf TensorFlow 1.15.5 TensorFlow 2.6.0 ONNX Runtime 1.8.1 Intel OpenVINO 2021.2 DCGM 2.2.9 FIL DALI 1.5		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.13.0 including TensorRT 8.0.1.6 PyTorch 1.10.0a0+3fd9dcf TensorFlow 1.15.5 TensorFlow 2.5.0 ONNX Runtime 1.8.1 Intel OpenVINO 2021.2 DCGM 2.2.8 FIL DALI 1.4		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.12.0 including TensorRT 8.0.1.6 PyTorch 1.9.0a0+c3d40fd TensorFlow 1.15.5 TensorFlow 2.5.0 ONNX Runtime 1.8.0 Intel OpenVINO 2021.2 DCGM 2.2.3 FIL DALI 1.3		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.11.0 including TensorRT 7.2.3.4 PyTorch 1.9.0a0+c3d40fd TensorFlow 1.15.5 TensorFlow 2.5.0 ONNX Runtime 1.8.0 Intel OpenVINO 2021.2 FIL DALI 1.2		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.10.0 including TensorRT 7.2.3.4 PyTorch 1.9.0a0+2ecb2c7 TensorFlow 1.15.5 TensorFlow 2.4.0 ONNX Runtime 1.7.1 Intel OpenVINO 2021.2		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.9.0 including TensorRT 7.2.3.4 PyTorch 1.9.0a0+2ecb2c7 TensorFlow 1.15.5 TensorFlow 2.4.0 ONNX Runtime 1.7.1 Intel OpenVINO 2021.2 DALI 1.0		In addition to the hardware listed above, Triton Inference Server also supports: AMD x86 CPU Intel x86 CPU 2.8.0 including TensorRT 7.2.2.3 PyTorch 1.9.0a0+df837d0 TensorFlow 1.15.5 TensorFlow 2.4.0 ONNX Runtime 1.6.0 Intel OpenVINO 2021.2 DALI 0.31		2.7.0 including TensorRT 7.2.2.3+cuda11.1.0.024 PyTorch 1.8.0a0+52ea372 TensorFlow 1.15.5 TensorFlow 2.4.0 ONNX Runtime 1.6.0 DALI 0.29
Triton Inference Server	Docker image size: 12.1 GB		Docker image size: 12.2 GB		Docker image size: 13.7 GB		Docker image size: 13.6 GB		Docker image size: 13.1 GB		Docker image size: 14.6 GB		Docker image size: 13.4 GB		Docker image size: 10.6 GB		Docker image size: 11.1 GB		Docker image size: 11.3 GB		Docker image size: 15.6 GB
TensorFlow For Jetson	TensorFlow 1.15.5 and 2.6.2 for Jetson		TensorFlow 1.15.5 and 2.6.0 for Jetson		TensorFlow 1.15.5 and 2.6.0 for Jetson		TensorFlow 1.15.5 and 2.6.0 for Jetson		TensorFlow 1.15.5 and 2.5.0 for Jetson		TensorFlow 1.15.5 and 2.5.0 for Jetson		TensorFlow 1.15.5 and 2.5.0 for Jetson		TensorFlow 1.15.5 and 2.4.0 for Jetson		TensorFlow 1.15.5 and 2.4.0 for Jetson		TensorFlow 1.15.5 and 2.4.0 for Jetson		TensorFlow 1.15.5 and 2.4.0 for Jetson
Triton for Jetson	Triton Inference Server 2.17.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.16.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.15.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.14.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.13.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.12.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.11.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.10.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.9.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.8.0 for Jetson AGX Xavier Nano TX2		Triton Inference Server 2.7.0 for Jetson

3. 20.xx Framework Containers Support Matrix

Important: Content that is included in <<>> brackets indicates new content from the previously published version.

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 20.06 release of an image was released in June, 2020.

20.xx container images

Table 3. Software stack packaged with the 20.xx container images
Container Image	20.12		20.11		20.10		20.09		20.08		20.07		20.06		20.03		20.02		20.01
DGX
DGX System	DGX-1 DGX-2 DGX A100 DGX Station		DGX-1 DGX-2 DGX A100 DGX Station		DGX-1 DGX-2 DGX A100 DGX Station		DGX-1 DGX-2 DGX A100 DGX Station		DGX-1 DGX-2 DGX A100 DGX Station		DGX-1 DGX-2 DGX A100 DGX Station		DGX-1 DGX-2 DGX Station		DGX-1 DGX-2 DGX Station		DGX-1 DGX-2 DGX Station		DGX-1 DGX-2
Operating System	DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹		DGX OS 4.1+¹ (4.6+ multi-node NCCL) 4.99.x (DGX A100) 5.0 Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+¹		DGX OS 4.1+ 4.99.x (DGX A100) Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+⁴		DGX OS 4.1+ 4.99.x (DGX A100) Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+		DGX OS 4.1+ 4.99.x (DGX A100) Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+		DGX OS 4.1+¹ Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+		DGX OS 4.1+¹ Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+		DGX OS 4.1+¹ Red Hat Enterprise Linux 7 / CentOS 7² EL7-20.02+		DGX OS 4.1+¹
NVIDIA Certified Systems
NVIDIA Driver	Release 20.12 is based on CUDA 11.1.1, which requires NVIDIA driver release 455.23. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx, 440.30, or 450.51. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.11 is based on CUDA 11.1.0, which requires NVIDIA driver release 455.23. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx, 440.30, or 450.51. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.10 is based on CUDA 11.1.0, which requires NVIDIA driver release 455.23. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx, 440.30, or 450.51. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.09 is based on CUDA 11.0.3, which requires NVIDIA driver release 450.51. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx or 440.30. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.08 is based on CUDA 11.0.3, which requires NVIDIA driver release 450.51. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx or 440.30. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.07 is based on CUDA 11.0.194, which requires NVIDIA driver release 450.51. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx or 440.30. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.06 is based on CUDA 11.0.167, which requires NVIDIA driver release 450.36. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx or 440.30. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.03 is based on CUDA 10.2.89, which requires NVIDIA driver release 440.33.01. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 396, 384.111+, 410, 418.xx or 440.30. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.02 is based on CUDA 10.2.89, which requires NVIDIA driver release 440.33.01. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 396, 384.111+, 410, 418.xx or 440.30. The CUDA driver's compatibility package only supports particular drivers. ³		Release 20.01 is based on CUDA 10.2.89, which requires NVIDIA driver release 440.33.01. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 396, 384.111+, 410, 418.xx or 440.30. The CUDA driver's compatibility package only supports particular drivers. ³
GPU Model	NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		NVIDIA Ampere GPU Architecture Turing Volta Pascal		Turing Volta Pascal		Turing Volta Pascal		Turing Volta Pascal
Base Container Image
Container OS	Ubuntu 20.04		Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04
CUDA	11.1.1		11.1.0		11.1.0		11.0.3		11.0.3		11.0.194		11.0.167		10.2.89		10.2.89		10.2.89
cuBLAS	11.3.0.106		11.2.1.74		11.2.1.74		11.2.0.252		11.2.0.252		11.1.0.229		11.1.0.213		10.2.2.89		10.2.2.89		10.2.2.89
cuDNN	8.0.5		8.0.4		8.0.4		8.0.4		8.0.2		8.0.1		8.0.1		7.6.5		7.6.5		7.6.5
NCCL	2.8.3		2.8.2		2.7.8		2.7.8		2.7.8		2.7.6		2.7.5		2.5.6		2.5.6		2.5.6
NVIDIA Optimized Frameworks
Kaldi	7905fe5a Python 3.8 MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.1.8 Nsight Systems 2020.3.4.32 TensorRT 7.2.2		edf6963c Python 3.6 MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 TensorRT 7.2.1		49dab837 Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 TensorRT 7.2.1		f88d5a36 Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 TensorRT 7.1.3		f88d5a36 Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 TensorRT 7.1.3		67db30cc Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.1.8 Nsight Systems 2020.3.2.6 TensorRT 7.1.3		2c7e78f Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.0.33 Nsight Systems 2020.2.5.8 TensorRT 7.1.2		da71f301 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorRT 7.0.0		5.5 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorRT 7.0.0		5.5 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorRT 7.0.0
Kaldi	Docker image size: 9.75 GB		Docker image size: 8.72 GB		Docker image size: 8.69 GB		Docker image size: 7.49 GB		Docker image size: 7.36 GB		Docker image size: 6.94 GB		Docker image size: 6.82 GB		Docker image size: 5.76 GB		Docker image size: 5.53 GB		Docker image size: 5.55 GB
NVCaffe															0.17.3 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorRT 7.0.0 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		0.17.3 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorRT 7.0.0 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		0.17.3 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorRT 7.0.0 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.1 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard
NVCaffe															Docker image size: 4.82 GB		Docker image size: 4.82 GB		Docker image size: 4.85 GB
DIGITS	6.1.1 including Python 3.8 MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.1.8 Nsight Systems 2020.3.4.32 TensorFlow 1.15.4 TensorRT 7.2.2		6.1.1 including Python 3.6 MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 TensorFlow 1.15.4 TensorRT 7.2.1		6.1.1 including Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 TensorFlow 1.15.4 TensorRT 7.2.1		6.1.1 including Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 TensorFlow 1.15.3 TensorRT 7.1.3		6.1.1 including Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 TensorFlow 1.15.3 TensorRT 7.1.3		6.1.1 including Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.1.8 Nsight Systems 2020.3.2.6 TensorFlow 1.15.3 TensorRT 7.1.3		6.1.1 including Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.0.33 Nsight Systems 2020.2.5.8 TensorFlow 1.15.2 TensorRT 7.1.2		6.1.1 including Python 3.6 NVCaffe 0.17.3 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorFlow 1.15.2 TensorRT 7.0.0		6.1.1 including Python 3.6 NVCaffe 0.17.3 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorFlow 1.15.2 TensorRT 7.0.0		6.1.1 including Python 3.6 NVCaffe 0.17.3 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorFlow 1.15.0 TensorRT 7.0.0
DIGITS	Docker image size: 16.1 GB		Docker image size: 15.3 GB		Docker image size: 15.2 GB		Docker image size: 13.3 GB		Docker image size: 12.9 GB		Docker image size: 12.4 GB		Docker image size with TensorFlow: 12.4 GB		Docker image size with TensorFlow: 10.5 GB Docker image size with Caffe: 5.06 GB		Docker image size with TensorFlow: 10.5 GB Docker image size with Caffe: 5.06 GB		Docker image size with TensorFlow: 9.36 GB Docker image size with Caffe: 5.01 GB
NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet	1.8.0.rc0 including Sockeye 2.2.3 MLNX_OFED 5.1 OpenMPI 4.0.5 Horovod 0.20.2 Nsight Compute 2020.2.1.8 Nsight Systems 2020.3.4.32 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.2 DALI 0.28 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.8.0.rc0 including Sockeye 2.2.3 MLNX_OFED 5.1 OpenMPI 4.0.5 Horovod 0.20.2 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.1 DALI 0.27 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.7.0 including ONNX exporter 0.1 Sockeye 2.1.16 MLNX_OFED OpenMPI 3.1.6 Horovod 0.19.1 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.2.1 DALI 0.26 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.7.0 including ONNX exporter 0.1 Sockeye 2.1.16 MLNX_OFED OpenMPI 3.1.6 Horovod 0.19.1 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 GluonCV Toolkit 0.7 GluonNLP Toolkit 0.8.1 TensorRT 7.1.3 DALI 0.25.1 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.6.0 including ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.6 Horovod 0.19.1 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 7.1.3 DALI 0.24 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.6.0 including ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.6 Horovod 0.19.1 Nsight Compute 2020.1.1.8 Nsight Systems 2020.3.2.6 GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 7.1.3 DALI 0.23 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.6.0 including ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.6 Horovod 0.19.1 Nsight Compute 2020.1.0.33 Nsight Systems 2020.2.5.8 GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 7.1.2 DALI 0.22 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.6.0 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.4 Horovod 0.19.0 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 DALI 0.19.0 GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 7.0.0 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.6.0.rc2 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.4 Horovod 0.19.0 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 DALI 0.18.0 Beta GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 7.0.0 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.6 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.5.1 commit c98184806 from September 4, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.4 Horovod 0.18.1 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 DALI 0.17.0 Beta GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 7.0.0 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.2 JupyterLab 1.2.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard
	Docker image size: 11.8 GB		Docker image size: 10.7 GB		Docker image size: 12.7 GB		Docker image size: 11.6 GB		Docker image size: 8.68 GB		Docker image size: 8.98 GB		Docker image size: 9.16 GB		Docker image size: 6.73 GB		Docker image size: 6.59 GB		Docker image size: 6.11 GB
PyTorch	1.8.0a0+1606899 including Python 3.8 APEX MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.1.8 Nsight Systems 2020.3.4.32 TensorBoard 1.15+nv TensorRT 7.2.2 DALI 0.28 MAGMA 2.5.2 DLProf 0.18.0 PyProf r20.12 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.8.0a0+17f8c32 including Python 3.6 APEX MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 TensorBoard 1.15+nv TensorRT 7.2.1 DALI 0.27 MAGMA 2.5.2 DLProf 0.17.0 PyProf r20.11 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.7.0a0+7036e91 including Python 3.6 APEX MLNX_OFED OpenMPI 4.0.5 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 TensorBoard 1.15+nv TensorRT 7.2.1 DALI 0.26 MAGMA 2.5.2 DLProf 0.16.0 PyProf r20.10 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.7.0a0+8deb4fe including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 TensorBoard 1.15+nv TensorRT 7.1.3 DALI 0.25.1 MAGMA 2.5.2 DLProf 0.15.0 PyProf r20.09 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.7.0a0+6392713 including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 TensorBoard 1.15+nv TensorRT 7.1.3 DALI 0.24 MAGMA 2.5.2 DLProf 0.14.0 PyProf r20.08 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.6.0a0+9907a3e including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.1.8 Nsight Systems 2020.3.2.6 TensorBoard 1.15+nv TensorRT 7.1.3 DALI 0.23 MAGMA 2.5.2 DLProf 0.13.0 PyProf r20.07 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard PyProf cb1099f6b		1.6.0a0+9907a3e including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.0.33 Nsight Systems 2020.2.5.8 TensorBoard 1.15+nv TensorRT 7.1.3 DALI 0.22 MAGMA 2.5.2 DLProf 0.12.0 PyProf r20.06 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.14 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.5.0a0+8f84ded including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorBoard 2.1.0 DALI 0.19.0 TensorRT 7.0.0 MAGMA 2.5.2 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.0.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.5.0a0+3bbb36e including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 TensorBoard 2.1.0 DALI 0.18.0 Beta TensorRT 7.0.0 MAGMA 2.5.2 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.0.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.4.0a0+a5b4d78 including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorBoard 2.1.0 DALI 0.17.0 Beta TensorRT 7.0.0 MAGMA 2.5.2 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.2 JupyterLab 1.0.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard
PyTorch	Docker image size: 14.2 GB		Docker image size: 13.2 GB		Docker image size: 12.9 GB		Docker image size: 11.1 GB		Docker image size: 12.2 GB		Docker image size: 11.9 GB		Docker image size: 11.9 GB		Docker image size: 9.41 GB		Docker image size: 9.11 GB		Docker image size: 9.12 GB
TensorFlow	2.3.1 including Python 3.8 Horovod 0.20.2 OpenMPI 4.0.5 TensorBoard 2.3.0+nv20.11 MLNX_OFED 5.1 TensorRT 7.2.2 DALI 0.28 Nsight Compute 2020.2.1.8 Nsight Systems 2020.3.4.32 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.4 including `20.12-tf1-py3`contains Python 3.8 Horovod 0.20.2 OpenMPI 4.0.5 TensorBoard 1.15.0+nv20.11 MLNX_OFED 5.1 OpenSeq2Seq at commit a81babd TensorRT 7.2.2 DALI 0.28 DLProf 0.18.0 Nsight Compute 2020.2.1.8 Nsight Systems 2020.3.4.32 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.3.1 including Python 3.6 Horovod 0.20.2 OpenMPI 4.0.5 TensorBoard 2.3.0+nv20.11 MLNX_OFED 5.1 TensorRT 7.2.1 DALI 0.27 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.4 including `20.11-tf1-py3`contains Python 3.6 Horovod 0.20.2 OpenMPI 4.0.5 TensorBoard 1.15.0+nv20.11 MLNX_OFED 5.1 OpenSeq2Seq at commit a81babd TensorRT 7.2.1 DALI 0.27 DLProf 0.17.0 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.3.1 including Python 3.6 Horovod 0.20.0 OpenMPI 3.1.6 TensorBoard 2.3.2 MLNX_OFED TensorRT 7.2.1 DALI 0.26 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.4 including `20.10-tf1-py3`contains Python 3.6 Horovod 0.20.0 OpenMPI 3.1.6 TensorBoard 1.15.0 MLNX_OFED OpenSeq2Seq at commit a81babd TensorRT 7.2.1 DALI 0.26 DLProf 0.15.0 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.3.0 including Python 3.6 Horovod 0.19.5 OpenMPI 3.1.6 TensorBoard 2.3.2 MLNX_OFED TensorRT 7.1.3 DALI 0.25.1 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.3 including `20.09-tf1-py3`contains Python 3.6 Horovod 0.19.1 OpenMPI 3.1.6 TensorBoard 2.2.2 MLNX_OFED OpenSeq2Seq at commit a81babd TensorRT 7.1.3 DALI 0.25.1 DLProf 0.15.0 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.2.0 including Python 3.6 Horovod 0.19.5 OpenMPI 3.1.6 TensorBoard 2.2.2 MLNX_OFED TensorRT 7.1.3 DALI 0.24 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.3 including `20.08-tf1-py3`contains Python 3.6 Horovod 0.19.1 OpenMPI 3.1.6 TensorBoard 2.2.2 MLNX_OFED OpenSeq2Seq at commit a81babd TensorRT 7.1.3 DALI 0.24 DLProf 0.14.0 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.2.0 including Python 3.6 Horovod 0.19.5 OpenMPI 3.1.6 TensorBoard 2.2.2 MLNX_OFED TensorRT 7.1.3 DALI 0.23 Nsight Compute 2020.1.1.8 Nsight Systems 2020.3.2.6 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.3 including `20.07-tf1-py3`contains Python 3.6 Horovod 0.19.1 OpenMPI 3.1.6 TensorBoard 2.2.2 MLNX_OFED OpenSeq2Seq at commit a81babd TensorRT 7.1.3 DALI 0.23 DLProf 0.13.0 Nsight Compute 2020.1.1.8 Nsight Systems 2020.3.2.6 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.2.0 including Python 3.6 Horovod 0.19.2 OpenMPI 3.1.6 TensorBoard 2.2.2 MLNX_OFED TensorRT 7.1.3 DALI 0.23 Nsight Compute 2020.1.0.33 Nsight Systems 2020.2.5.8 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.2 including `20.06-tf1-py3`contains Python 3.6 Horovod 0.19.1 OpenMPI 3.1.6 TensorBoard 2.2.2 MLNX_OFED OpenSeq2Seq at commit a81babd TensorRT 7.1.2 DALI 0.22 DLProf 0.12.0 Nsight Compute 2020.1.0.33 Nsight Systems 2020.2.5.8 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.1.0 including Python 3.6 Horovod 0.19.0 OpenMPI 3.1.4 TensorBoard 2.1.0 MLNX_OFED TensorRT 7.0.0 NCCL 2.6.3 DALI 0.19.0 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.2 including `20.03-tf1-py3` contains Python 3.6 Horovod 0.19.0 OpenMPI 3.1.4 TensorBoard 1.15.0+nv MLNX_OFED OpenSeq2Seq at commit a81babd TensorRT 7.0.0 NCCL 2.6.3 DALI 0.19.0 DLProf 0.10.0 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 6.0.0 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.7 Jupyter-TensorBoard	2.1.0 including Python 3.6 Horovod 0.19.0 OpenMPI 3.1.4 TensorBoard 2.1.0 MLNX_OFED TensorRT 7.0.0 DALI 0.18.0 Beta Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.2 including `20.02-tf1-py3` contains Python 3.6 Horovod 0.19.0 OpenMPI 3.1.4 TensorBoard 1.15.0+nv MLNX_OFED OpenSeq2Seq at commit a81babd TensorRT 7.0.0 DALI 0.18.0 Beta DLProf 20.02 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.3 JupyterLab 1.2.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard	2.0.0 including Python 3.6 Horovod 0.18.2 OpenMPI 3.1.4 TensorBoard 2.0.2 MLNX_OFED TensorRT 7.0.0 DALI 0.17.0 Beta Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.0 including `20.01-tf1-py2` contains Python 2.7 or `20.01-tf1-py3` contains Python 3.6 Horovod 0.18.2 OpenMPI 3.1.4 TensorBoard 1.15.0+nv MLNX_OFED OpenSeq2Seqat commit a81babd TensorRT 7.0.0 DALI 0.17.0 Beta DLProf 20.01 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.2 JupyterLab 1.2.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard
TensorFlow	Docker image size: 12.2 GB	Docker image size: 15.2 GB	Docker image size: 11.6 GB	Docker image size: 14.4 GB	Docker image size: 11.4 GB	Docker image size: 14.3 GB	Docker image size: 9.62 GB	Docker image size: 12.4 GB	Docker image size: 11 GB	Docker image size: 11.9 GB	Docker image size: 9.3 GB	Docker image size: 11.5 GB	Docker image size: 9.45 GB	Docker image size: 11.5 GB	Docker image size: 8.05 GB	Docker image size: 9.53 GB	Docker size image: 7.42 GB	Docker size image: 9.49 GB	Docker size image: 7.15 GB	Docker image size with Python 2.7: 7.88 GB Docker image size with Python 3.6: 8.39 GB
TensorRT	7.2.2 including: Python 3.8 MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.1.8 Nsight Systems 2020.3.4.32		7.2.1 including: Python 3.6 MLNX_OFED 5.1 OpenMPI 4.0.5 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32		7.2.1 including: Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.2.0.18 Nsight Systems 2020.3.4.32		7.1.3 including: Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6		7.1.3 including: Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.2.4 Nsight Systems 2020.3.2.6		7.1.3 including: Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.1.8 Nsight Systems 2020.3.2.6		7.1.2 including: Python 3.6 MLNX_OFED OpenMPI 3.1.6 Nsight Compute 2020.1.0.33 Nsight Systems 2020.2.5.8		7.0.0 including: Python 2.7 or Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1		7.0.0 including: Python 2.7 or Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2020.1.1		7.0.0 including: Python 2.7 or Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1
TensorRT	Docker image size: 7.09 GB		Docker image size: 6.96 GB		Docker image size: 6.93 GB		Docker image size: 5.75 GB		Docker image size: 5.63 GB		Docker image size: 5.57 GB		Docker image size: 4.97 GB		Docker image size with Python 2.7: 4.05 GB Docker image size with Python 3.6: 4.08 GB		Docker image size with Python 2.7: 4.04 GB Docker image size with Python 3.6: 4.07 GB		Docker image size with Python 2.7: 4.08 GB Docker image size with Python 3.6: 4.11 GB
Triton Inference Server	2.6.0 including TensorRT 7.2.2 PyTorch 1.8.0a0+1606899 TensorFlow 1.15.4 TensorFlow 2.3.1 ONNX Runtime 1.5.3 DALI 0.28		2.5.0 including TensorRT 7.2.1 PyTorch 1.8.0a0+17f8c32 TensorFlow 1.15.4 TensorFlow 2.3.1 ONNX Runtime 1.5.3 DALI 0.27		2.4.0 including TensorRT 7.2.1 PyTorch 1.7.0a0+6392713 TensorFlow 1.15.4 TensorFlow 2.3.1 ONNX Runtime 1.4.0 DALI 0.26		2.3.0 including TensorRT 7.1.3 PyTorch 1.7.0a0+6392713 TensorFlow 1.15.3 TensorFlow 2.3.0 ONNX Runtime 1.4.0		2.3.0 including TensorRT 7.1.3 1.7.0a0+6392713 TensorFlow 1.15.3 TensorFlow 2.2.0 ONNX Runtime 1.4.0		1.15.0 and 2.1.0 and including TensorRT 7.1.3 PyTorch 1.6.0a0+9907a3e TensorFlow 1.15.3 ONNX Runtime 1.3.0		1.14.0 and 2.0.0 including TensorRT 7.1.2 PyTorch 1.6.0a0+9907a3e TensorFlow 1.15.2 ONNX Runtime 1.3.0		1.12.0 including MLNX_OFED OpenMPI 3.1.4 TensorRT 7.0.0		1.11.0 including MLNX_OFED OpenMPI 3.1.4 TensorRT 7.0.0		1.10.0 including MLNX_OFED OpenMPI 3.1.4 TensorRT 7.0.0
Triton Inference Server	Docker image size: 15.6 GB		Docker image size: 11.55 GB		Docker image size: 11.3 GB		Docker image size: 8.3 GB		Docker image size: 9.97 GB		Docker image size: 8.22 GB		Docker image size for 1.14.0: 9.73 GB	Docker image size for 2.0.0: 8.68 GB	Docker image size: 6.31 GB		Docker image size: 6.07 GB		Docker image size: 6.16 GB
TensorFlow For Jetson	TensorFlow 1.15.4 and 2.3.1 for Jetson		TensorFlow 1.15.4 and 2.3.1 for Jetson		TensorFlow 1.15.4 and 2.3.1 for Jetson		TensorFlow 1.15.3 and 2.3.0 for Jetson		TensorFlow 1.15.3 and 2.2.0 for Jetson		TensorFlow 1.15.3 and 2.2.0 for Jetson		TensorFlow 1.15.2 and 2.1.0 for Jetson		TensorFlow 1.15.2 and 2.1.0 for Jetson		TensorFlow 1.15.2 and 2.1.0 for Jetson		TensorFlow 1.15.0 and 2.0.0 for Jetson
Triton for Jetson	Triton Inference Server 2.6.0 for Jetson		Triton Inference Server 2.5.0 for Jetson		Triton Inference Server 2.4.0 for Jetson

4. 19.xx Framework Containers Support Matrix

Important: Content that is included in <<>> brackets indicates new content from the previously published version.

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 19.01 release of an image was released in January, 2019.

19.xx container images

Table 4. Software stack packaged with the 19.xx container images
	Container Image	19.12		19.11		19.10	19.09	19.08	19.07	19.06	19.05	19.04	19.03	19.02	19.01
Supported Platform	Host OS	DGX OS Server 4.1.0+ (DGX-1)⁵ 4.1.0+ (DGX-2) DGX OS Desktop 4.1.0+ (DGX Station)¹		DGX OS Server 4.1.0+ (DGX-1)¹ 4.1.0+ (DGX-2) DGX OS Desktop 4.1.0+ (DGX Station)¹		DGX OS Server 4.1.0+ (DGX-1)¹ 4.1.0+ (DGX-2) DGX OS Desktop 4.1.0+ (DGX Station)¹	DGX OS Server 4.1.0+, 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)¹ 4.1.0+, 4.0.1+ (DGX-2) DGX OS Desktop 4.1.0+, 4.0.4+ and 3.1.2+ (DGX Station)¹	DGX OS Server 4.1.0+, 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)¹ 4.1.0+, 4.0.1+ (DGX-2) DGX OS Desktop 4.1.0+, 4.0.4+ and 3.1.2+ (DGX Station)¹	DGX OS Server 4.1.0+, 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)¹ 4.1.0+, 4.0.1+ (DGX-2) DGX OS Desktop 4.1.0+, 4.0.4+ and 3.1.2+ (DGX Station)¹	DGX OS Server 4.1.0+, 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)¹ 4.1.0+, 4.0.1+ (DGX-2) DGX OS Desktop 4.1.0+, 4.0.4+ and 3.1.2+ (DGX Station)¹	DGX OS Server 4.1.0+, 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)¹ 4.1.0+, 4.0.1+ (DGX-2) DGX OS Desktop 4.1.0+, 4.0.4+ and 3.1.2+ (DGX Station)¹	DGX OS Server 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 4.0.4+ and 3.1.2+ (DGX Station)	DGX OS Server 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 4.0.4+ and 3.1.2+ (DGX Station)	DGX OS Server 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 4.0.4+ and 3.1.2+ (DGX Station)	DGX OS Server 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 4.0.4+ and 3.1.2+ (DGX Station)
Supported Platform	NVIDIA Driver	Release 19.12 is based on CUDA 10.2.89, which requires NVIDIA driver release 440.33.01. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 396, 384.111+, 410, 418.xx or 440.30 The CUDA driver's compatibility package only supports particular drivers. ³		Release 19.11 is based on CUDA 10.2.89, which requires NVIDIA driver release 440.xx. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 396, 384.111+, 410 or 418.xx. The CUDA driver's compatibility package only supports particular drivers. ²		Release 19.10 is based on CUDA 10.1.243, which requires NVIDIA driver release 418.xx. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 396, 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.09 is based on CUDA 10.1.243, which requires NVIDIA driver release 418.xx. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 396, 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.08 is based on CUDA 10.1.243, which requires NVIDIA driver release 418.87. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.07 is based on CUDA 10.1.168, which requires NVIDIA driver release 418.67. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.06 is based on CUDA 10.1.168, which requires NVIDIA driver release 418.xx. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.05 is based on CUDA 10.1 Update 1, which requires NVIDIA driver release 418.xx. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.04 is based on CUDA 10.1, which requires NVIDIA driver release 418.xx.x+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.03 is based on CUDA 10.1, which requires NVIDIA driver release 418.xx+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.02 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+. The CUDA driver's compatibility package only supports particular drivers. ²	Release 19.01 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+. The CUDA driver's compatibility package only supports particular drivers. ²
Supported Hardware	GPU Model	Turing Volta Pascal		Turing Volta Pascal		Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal
Base Image	Container OS	Ubuntu 18.04		Ubuntu 18.04		Ubuntu 18.04	Ubuntu 18.04	Ubuntu 18.04	Ubuntu 18.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04
	CUDA	10.2.89		10.2.89		10.1.243	10.1.243	10.1.243	10.1.168	10.1.168	10.1 Update 1	10.1.105	10.1.105	10.0.130	10.0.130
	cuBLAS	10.2.2.89		10.2.2.89		10.2.1.243	10.2.1.243	10.2.1.243	10.2.0.168	10.2.0.168	10.1 Update 1	10.1.0.105	10.1.105	10.0.130	10.0.130
	cuDNN	7.6.5		7.6.5		7.6.4	7.6.3	7.6.2	7.6.1	7.6.0	7.6.0	7.5.0	7.5.0	7.4.2	7.4.2
	NCCL	2.5.6		2.5.6		2.4.8	2.4.8	2.4.8	2.4.7	2.4.7	2.4.6	2.4.6	2.4.3	2.3.7	2.3.7
NVIDIA Optimized Frameworks	Kaldi	5.5 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorRT 6.0.1		5.5 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.5.2 TensorRT 6.0.1		5.5 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.5.1 TensorRT 6.0.1	5.5 including Python 3.5 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.4.2 TensorRT 6.0.1	5.5 including Python 3.5 MLNX_OFED +4.0 OpenMPI 3.1.4 Nsight Compute 10.1.168 Nsight Systems 2019.3.7.9 TensorRT 5.1.5	5.5 including Python 3.5 MLNX_OFED +3.4 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.6.30 TensorRT 5.1.5	5.5 including Python 3.5 OpenMPI 3.1.3 TensorRT 5.1.5 Nsight Compute 10.1.168 Nsight Systems 2019.3.1.94	5.5 including Python 3.5 Nsight Compute 10.1.163 Nsight Systems 2019.3.1.94 OpenMPI 3.1.3 TensorRT 5.1.5	5.5 including Python 3.5 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 2019.3.1.8 TensorRT 5.1.2 RC	5.5 including Python 3.5 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 10.1.105 TensorRT 5.1.2 RC
	Kaldi	Docker image size: 5.49 GB		Docker image size: 5.61 GB		Docker image size: 5.63 GB	Docker image size: 5.57 GB	Docker image size: 5.57 GB	Docker image size: 5.00 GB	Docker image size: 5.11 GB	Docker image size: 5.11 GB	Docker image size: 5.01 GB	Docker image size: 5.09 GB
	NVCaffe	0.17.3 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorRT 6.0.1 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.1 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		0.17.3 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.5.2 TensorRT 6.0.1 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.1 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard		0.17.3 including Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.5.1 TensorRT 6.0.1 Jupyter and JupyterLab: Jupyter Client 5.3.3 Jupyter Core 4.5.0 Jupyter Notebook 6.0.1 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard	0.17.3 including Python 2.7 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.4.2 TensorRT 6.0.1 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 6.0.1 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard	0.17.3 including Python 2.7 MLNX_OFED +4.0 OpenMPI 3.1.4 Nsight Compute 10.1.168 Nsight Systems 2019.3.7.9 TensorRT 5.1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 Jupyter Notebook 6.0.0 JupyterLab 1.0.5 JupyterLab Server 1.0.0 Jupyter-TensorBoard	0.17.3 including Python 2.7 MLNX_OFED +3.4 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.6.30 TensorRT 5.1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	0.17.3 including Python 2.7 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.1.94 TensorRT 5.1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.6 JupyterLab Server 0.2.0	0.17.3 including Python 2.7 OpenMPI 3.1.3 Nsight Compute 10.1.163 Nsight Systems 2019.3.1.94 TensorRT 5.1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.4 JupyterLab Server 0.2.0	0.17.3 including Python 2.7 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 2019.3.1.8 TensorRT 5.1.2 RC Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.4 JupyterLab Server 0.2.0	0.17.3 including Python 2.7 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 10.1.105 TensorRT 5.1.2 RC Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.4 JupyterLab Server 0.2.0	0.17.2 including Python 2.7 OpenMPI 3.1.3 TensorRT 5.0.2 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.4 JupyterLab Server 0.2.0	0.17.2 including Python 2.7 OpenMPI 3.1.3 TensorRT 5.0.2
	NVCaffe	Docker image size: 4.81 GB		Docker image size: 5.02 GB		Docker image size: 5.1 GB	Docker image size: 5.02 GB	Docker image size: 5.02 GB	Docker image size: 4.45 GB	Docker image size: 4.33 GB	Docker image size: 4.33 GB	Docker image size: 4.29 GB	Docker image size: 4.42 GB	Docker image size: 3.56 GB	Docker image size: 3.51 GB
	DIGITS	6.1.1 including Python 3.6 NVCaffe 0.17.3 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorFlow 1.15.0 TensorRT 6.0.1		NA		6.1.1 including Python 2.7 NVCaffe 0.17.3 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.5.1 TensorFlow 1.14.0 TensorRT 6.0.1	6.1.1 including Python 2.7 NVCaffe 0.17.3 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.4.2 TensorFlow 1.14.0 TensorRT 6.0.1	6.1.1 including Python 2.7 NVCaffe 0.17.3 MLNX_OFED +4.0 OpenMPI 3.1.4 Nsight Compute 10.1.168 Nsight Systems 2019.3.7.9 TensorFlow 1.14.0 TensorRT 5.1.5	6.1.1 including Python 2.7 NVCaffe 0.17.3 MLNX_OFED +3.4 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.6.30 TensorFlow 1.14.0 TensorRT 5.1.5	6.1.1 including Python 2.7 NVCaffe 0.17.3 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.1.94 TensorFlow 1.13.1 TensorRT 5.1.5	6.1.1 including Python 2.7 NVCaffe 0.17.3 OpenMPI 3.1.3 Nsight Compute 10.1.163 Nsight Systems 2019.3.1.94 TensorFlow 1.13.1 TensorRT 5.1.5	6.1.1 including Python 2.7 NVCaffe 0.17.3 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 2019.3.1.8 TensorFlow 1.13.1 TensorRT 5.1.2 RC	6.1.1 including Python 2.7 NVCaffe 0.17.3 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 10.1.105 TensorFlow 1.13.1 TensorRT 5.1.2 RC	6.1.1 including Python 2.7 NVCaffe 0.17.2 OpenMPI 3.1.3 TensorFlow 1.13.0-rc0 TensorRT 5.0.2	6.1.1 including Python 2.7 NVCaffe 0.17.2 OpenMPI 3.1.3 TensorFlow 1.12.0 TensorRT 5.0.2
	DIGITS	Docker image size with TensorFlow: 9.3 GB Docker image size with Caffe: 4.97 GB		NA		Docker image size with TensorFlow: 8.78 GB Docker image size with Caffe: 5.22 GB	Docker image size with TensorFlow: 7.74 GB Docker image size with Caffe: 5.13 GB	Docker image size with TensorFlow: 7.74 GB Docker image size with Caffe: 5.13 GB	Docker image size with TensorFlow: 7.14 GB Docker image size with Caffe: 4.57 GB	Docker image size with TensorFlow: 7.86 GB Docker image size with Caffe: 4.45 GB	Docker image size with TensorFlow: 7.00 GB Docker image size with Caffe: 4.45 GB	Docker image size with TensorFlow: 7.04 GB Docker image size with Caffe: 4.41 GB	Docker image size with TensorFlow: 6.92 GB Docker image size with Caffe: 4.49 GB	Docker image size with TensorFlow: 6.43 GB Docker image size with Caffe: 3.70 GB	Docker image size with TensorFlow: 5.96 GB Docker image size with Caffe: 3.66 GB
	NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet	1.5.1 commit c98184806 from September 4, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.4 Horovod 0.18.1 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 DALI 0.16.0 Beta GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 6.0.1 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.2 JupyterLab 1.2.3 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.5.1 commit c98184806 from September 4, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.4 Horovod 0.18.1 Nsight Compute 2019.5.0 Nsight Systems 2019.5.2 DALI 0.15.0 Beta GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 6.0.1 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.2 JupyterLab 1.2.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.5.1 commit c98184806 from September 4, 2019 including Python 3.6 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.4 Horovod 0.18.1 Nsight Compute 2019.4.0 Nsight Systems 2019.5.1 DALI 0.14.0 Beta GluonCV Toolkit 0.5 GluonNLP Toolkit 0.8.1 TensorRT 6.0.1 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.3 Jupyter Core 4.5.0 Jupyter Notebook 6.0.1 JupyterLab 1.1.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard	1.5.0 commit 006486af3 from August 28, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED OpenMPI 3.1.4 Horovod 0.18.1 Nsight Compute 2019.4.0 Nsight Systems 2019.4.2 DALI 0.13.0 Beta GluonCV Toolkit 0.4 GluonNLP Toolkit 0.8.1 TensorRT 6.0.1 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 6.0.1 JupyterLab 1.1.1 JupyterLab Server 1.0.6 Jupyter-TensorBoard	1.5.0 commit 75a9e187d from June 27, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED +4.0 OpenMPI 3.1.4 Horovod 0.16.4 Nsight Compute 10.1.168 Nsight Systems 2019.3.7.9 DALI 0.12.0 Beta GluonCV Toolkit 0.4 GluonNLP Toolkit 0.7.1 TensorRT 5.1.5 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 Jupyter Notebook 6.0.0 JupyterLab 1.0.5 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.5.0.rc2 including upstream commits up through commit 75a9e187d from June 27, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.99 MLNX_OFED +3.4 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.6.30 Horovod 0.16.2 DALI 0.11.0 Beta TensorRT 5.1.5 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 JupyterLab 1.0.0 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.4.1 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.61 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.1.94 Horovod 0.16.2 DALI 0.10.0 Beta TensorRT 5.1.5 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.6 JupyterLab Server 0.2.0	1.4.0 commit 87c7addcd from February 12, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.61 OpenMPI 3.1.3 Horovod 0.16.1 Nsight Compute 10.1.163 Nsight Systems 2019.3.1.94 DALI 0.9.1 Beta TensorRT 5.1.5 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.4.0 commit 87c7addcd from February 12, 2019 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.61 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 2019.3.1.8 Horovod 0.13.11 DALI 0.8.1 Beta TensorRT 5.1.2 RC Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.4.0 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.61 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 10.1.105 Horovod 0.13.11 DALI 0.7 Beta TensorRT 5.1.2 RC Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.4.0.rc0 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.61 OpenMPI 3.1.3 Horovod 0.13.11 TensorRT 5.0.2 DALI 0.6.1 Beta Tensor Core optimized example: ResNet50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.4.0.rc0 including Python 3.5 ONNX exporter 0.1 Sockeye 1.18.61 OpenMPI 3.1.3 Horovod 0.13.11 TensorRT 5.0.2 DALI 0.6 Beta Tensor Core optimized example: ResNet50 v1.5
		Docker image size: 6.05 GB		Docker image size: 6.14 GB		Docker image size: 6.2 GB	Docker image size: 5.75 GB	Docker image size: 5.75 GB	Docker image size: 5.11 GB	Docker image size: 4.99 GB	Docker image size: 4.95 GB	Docker image size: 4.9 GB	Docker image size: 4.73 GB	Docker image size: 3.83 GB	Docker image size: 3.82 GB
	PyTorch	1.4.0a0+a5b4d78 including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 TensorBoard 2.1.0 DALI 0.16.0 Beta TensorRT 6.0.1 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.2 JupyterLab 1.0.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.4.0a0+174e1ba including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.5.2 TensorBoard 2.0.1 DALI 0.15.0 Beta TensorRT 6.0.1 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext TransformerXL Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard		1.3.0a0+24ae9b5 including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.5.1 TensorBoard 2.0.0 DALI 0.14.0 Beta TensorRT 6.0.1 Tensor Core optimized examples: ResNeXt101-32x4d SE-ResNext Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.3 Jupyter Core 4.5.0 Jupyter Notebook 6.0.1 JupyterLab 1.0.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard	1.2.0 including Python 3.6 APEX MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.4.2 TensorBoard 1.14.0+nv DALI 0.12.0 Beta TensorRT 6.0.1 Tensor Core optimized examples: Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 6.0.1 JupyterLab 1.0.4 JupyterLab Server 1.0.6 Jupyter-TensorBoard	1.2.0a0 including upstream commits up through commit 9130ab38 from July 31, 2019 as well as a cherry-picked performance fix 9462ca29 including Python 3.6 APEX MLNX_OFED +4.0 OpenMPI 3.1.4 Nsight Compute 10.1.168 Nsight Systems 2019.3.7.9 TensorBoard 1.14.0+nv DALI 0.12.0 Beta TensorRT 5.1.5 Tensor Core optimized examples: Jasper BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 Jupyter Notebook 6.0.0 JupyterLab 1.0.4 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.2.0a0 including upstream commits up through commit f6aac41 from June 19, 2019 including Python 3.6 APEX MLNX_OFED +3.4 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.6.30 TensorBoard 1.14.0+nv DALI 0.11.0 Beta TensorRT 5.1.5 Tensor Core optimized examples: BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.1.0 commit 0885dd28 from May 28, 2019 including Python 3.6 APEX OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.1.94 DALI 0.10.0 Beta TensorRT 5.1.5 Tensor Core optimized examples: BERT Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.6 JupyterLab Server 0.2.0	1.0.1 commit 828a6a3b from March 31, 2019 including Python 3.6 APEX OpenMPI 3.1.3 Nsight Compute 10.1.163 Nsight Systems 2019.3.1.94 DALI 0.9.1 Beta TensorRT 5.1.5 Tensor Core optimized examples: Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.0.1 commit 9eb0f43 from March 28, 2019 including Python 3.6 APEX OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 2019.3.1.8 DALI 0.8.1 Beta TensorRT 5.1.2 RC Tensor Core optimized examples: Mask R-CNN Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.1.0a0+81e025d including Python 3.6 APEX OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 10.1.105 DALI 0.7 Beta TensorRT 5.1.2 RC Tensor Core optimized examples: Tacotron 2 and WaveGlow v1.1 SSD300 v1.1 Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.1.0a0+c42431b including Python 3.6 APEX OpenMPI 3.1.3 DALI 0.6.1 Beta TensorRT 5.0.2 Tensor Core optimized examples: Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.0.0 including Python 3.6 Caffe2 APEx OpenMPI 3.1.3 DALI 0.6 Beta Tensor Core optimized examples: Neural Collaborative Filtering (NCF) Transformer ResNet50 v1.5 GNMT v2 TensorRT 5.0.2
	PyTorch	Docker image size: 9.28 GB		Docker image size: 9.21 GB		Docker image size: 9.32 GB	Docker image size: 9 GB	Docker image size: 9 GB	Docker image size: 8.33 GB	Docker image size: 7.7 GB	Docker image size: 7.55 GB	Docker image size: 7.45 GB	Docker image size: 7.71 GB	Docker image size: 6.61 GB	Docker image size: 7.70 GB
	TensorFlow	2.0.0 including Python 3.6 Horovod 0.18.2 OpenMPI 3.1.4 TensorBoard 2.0.2 MLNX_OFED TensorRT 6.0.1 DALI 0.16.0 Beta Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.0 including `19.12-tf1-py2` contains Python 2.7 or `19.12-tf1-py3` contains Python 3.6 Horovod 0.18.2 OpenMPI 3.1.4 TensorBoard 1.15.0+nv MLNX_OFED OpenSeq2Seqat commit a81babd TensorRT 6.0.1 DALI 0.16.0 Beta DLProf 19.12 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 6.0.2 JupyterLab 1.2.2 JupyterLab Server 1.0.6 Jupyter-TensorBoard	2.0.0 including Python 3.6 Horovod 0.18.1 OpenMPI 3.1.4 TensorBoard 2.0.1 MLNX_OFED TensorRT 6.0.1 DALI 0.15.0 Beta Nsight Compute 2019.5.0 Nsight Systems 2019.5.2 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.15.0 including `19.11-tf1-py2` contains Python 2.7 or `19.11-tf1-py3` contains Python 3.6 Horovod 0.18.1 OpenMPI 3.1.4 TensorBoard 1.15.0+nv MLNX_OFED OpenSeq2Seqat commit a81babd TensorRT 6.0.1 DALI 0.15.0 Beta DLProf 19.11 Nsight Compute 2019.5.0 Nsight Systems 2019.5.2 Tensor Coreoptimized examples: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.4 Jupyter Core 4.6.1 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.14.0 including Python 2.7 or Python 3.6 Horovod 0.18.1 OpenMPI 3.1.4 TensorBoard 1.14.0+nv MLNX_OFED OpenSeq2Seq at commit 2e0b1d8 TensorRT 6.0.1 DALI 0.14.0 Beta DLProf 19.10 Nsight Compute 2019.4.0 Nsight Systems 2019.5.1 Tensor Core optimized example: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.3 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.14.0 including Python 2.7 or Python 3.6 Horovod 0.18.0 OpenMPI 3.1.4 TensorBoard 1.14.0+nv MLNX_OFED OpenSeq2Seq at commit 2e0b1d8 TensorRT 6.0.1 DALI 0.13.0 Beta DLProf 19.09 Nsight Compute 2019.4.0 Nsight Systems 2019.4.2 Tensor Core optimized example: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.14.0 including Python 2.7 or Python 3.6 Horovod 0.16.2 OpenMPI 3.1.4 TensorBoard 1.14.0+nv MLNX_OFED +4.0 OpenSeq2Seq at commit 2e0b1d8 TensorRT 5.1.5 DALI 0.12.0 Beta DLProf 19.08 Nsight Compute 10.1.168 Nsight Systems 2019.3.7.9 Tensor Core optimized example: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 JupyterLab 1.0.2 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.14.0 including Python 2.7 or Python 3.6 Horovod 0.16.2 OpenMPI 3.1.3 TensorBoard 1.14.0+nv MLNX_OFED +3.4 OpenSeq2Seq at commit 27346d1 TensorRT 5.1.5 DALI 0.11.0 Beta DLProf 19.07 Nsight Compute 10.1.168 Nsight Systems 2019.3.6.30 Tensor Core optimized example: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.3.1 Jupyter Core 4.5.0 Jupyter Notebook 5.7.8 JupyterLab 1.0.1 JupyterLab Server 1.0.0 Jupyter-TensorBoard	1.13.1 including Python 2.7 or Python 3.5 Horovod 0.16.2 OpenMPI 3.1.3 TensorBoard 1.13.1+nv MLNX_OFED 3.4 OpenSeq2Seq at commit 27346d1 TensorRT 5.1.5 DALI 0.10.0 Beta DLProf 19.06 Nsight Compute 10.1.168 Nsight Systems 2019.3.1.94 Tensor Core optimized example: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 Jupyter Notebook 5.7.8 JupyterLab 0.35.6 JupyterLab Server 0.2.0	1.13.1 including Python 2.7 or Python 3.5 Horovod 0.16.1 OpenMPI 3.1.3 TensorBoard 1.13.1 MLNX_OFED 3.4 OpenSeq2Seq TensorRT 5.1.5 DALI 0.9.1 Beta Nsight Compute 10.1.163 Nsight Systems 2019.3.1.94 Tensor Core optimized example: U-Net Medical SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.13.1 including Python 2.7 or Python 3.5 Horovod 0.16.1 OpenMPI 3.1.3 TensorBoard 1.13.1 MLNX_OFED 3.4 OpenSeq2Seq TensorRT 5.1.2 RC DALI 0.8.1 Beta Nsight Compute 10.1.105 Nsight Systems 2019.3.1.8 Tensor Core optimized example: SSD320 v1.2 Neural Collaborative Filtering (NCF) BERT U-Net Industrial Defect Segmentation GNMT v2 ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.13.1 including Python 2.7 or Python 3.5 Horovod 0.16.0 OpenMPI 3.1.3 TensorBoard 1.13.1 MLNX_OFED 3.4 OpenSeq2Seq TensorRT 5.1.2 RC DALI 0.7 Beta Nsight Compute 10.1.105 Nsight Systems 10.1.105 Tensor Core optimized example: ResNet-50 v1.5 Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.13.0-rc0 including Python 2.7 or Python 3.5 Horovod 0.15.1 OpenMPI 3.1.3 TensorBoard 1.12.2 MLNX_OFED 3.4 OpenSeq2Seq v8.12 TensorRT 5.0.2 DALI 0.6.1 Beta Jupyter and JupyterLab: Jupyter Client 5.2.4 Jupyter Core 4.4.0 JupyterLab 0.35.4 JupyterLab Server 0.2.0	1.12.0 including Python 2.7 or Python 3.5 Horovod 0.15.1 OpenMPI 3.1.3 TensorBoard 1.12.0 MLNX_OFED 3.4 OpenSeq2Seq v19.01 TensorRT 5.0.2 DALI 0.6 Beta
	TensorFlow	Docker size image: 7.71 GB	Docker image size with Python 2.7: 7.84 GB Docker image size with Python 3.6: 8.32 GB	Docker image size: 7.78	Docker image size with Python 2.7: 8.02 GB Docker image size with Python 3.6: 8.60 GB	Docker image size with Python 2.7: 7.81 GB Docker image size with Python 3.6: 8.38 GB	Docker image size with Python 2.7: 6.78 GB Docker image size with Python 3.6: 7.34 GB	Docker image size with Python 2.7: 6.78 GB Docker image size with Python 3.6: 7.34 GB	Docker image size with Python 2.7: 6.18 GB Docker image size with Python 3.6: 6.71 GB	Docker image size: 6.88 GB	Docker image size: 6.76 GB	Docker image size: 6.8 GB	Docker image size: 6.72 GB	Docker image size: 6.06 GB	Docker image size: 5.57 GB
	TensorRT	6.0.1 including: Python 2.7 or Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.6.1		6.0.1 including: Python 2.7 or Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.5.0 Nsight Systems 2019.5.2		6.0.1 including: Python 2.7 or Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.5.1	6.0.1 including: Python 2.7 or Python 3.6 MLNX_OFED OpenMPI 3.1.4 Nsight Compute 2019.4.0 Nsight Systems 2019.4.2	5.1.5 including: Python 2.7 or Python 3.6 MLNX_OFED +4.0 OpenMPI 3.1.4 Nsight Compute 10.1.168 Nsight Systems 2019.3.7.9	5.1.5 including: Python 2.7 or Python 3.5 MLNX_OFED +3.4 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.6.30	5.1.5 including: Python 2.7 or Python 3.5 OpenMPI 3.1.3 Nsight Compute 10.1.168 Nsight Systems 2019.3.1.94	5.1.5 including: Python 2.7 or Python 3.5 OpenMPI 3.1.3 Nsight Compute 10.1.163 Nsight Systems 2019.3.1.94	5.1.2 RC including: Python 2.7 or Python 3.5 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 2019.3.1.8	5.1.2 RC including: Python 2.7 or Python 3.5 OpenMPI 3.1.3 Nsight Compute 10.1.105 Nsight Systems 10.1.105	5.0.2 including: Python 2.7 or Python 3.5 OpenMPI 3.1.3	5.0.2 including: Python 2.7 or Python 3.5 OpenMPI 3.1.3
	TensorRT	Docker image size Python 2.7: 4.03 GB Docker image size with Python 3.6: 4.06 GB		Docker image size Python 2.7: 3.83 GB Docker image size with Python 3.6: 4.16 GB		Docker image size: 4.2 GB	Docker image size: 4.4 GB	Docker image size: 4.4 GB	Docker image size: 3.83 GB	Docker image size: 3.83 GB	Docker image size: 3.83 GB	Docker image size: 3.79 GB	Docker image size: 3.91 GB	Docker image size: 3.01 GB	Docker image size: 3.00 GB
	TensorRT Inference Server	1.9.0 including MLNX_OFED OpenMPI 3.1.4 TensorRT 6.0.1		1.8.0 including MLNX_OFED OpenMPI 3.1.4 TensorRT 6.0.1		1.7.0 including MLNX_OFED OpenMPI 3.1.4 TensorRT 6.0.1	1.6.0 including MLNX_OFED OpenMPI 3.1.4 TensorRT 6.0.1	1.5.0 including MLNX_OFED +4.0 OpenMPI 3.1.4 TensorRT 5.1.5	1.4.0 including MLNX_OFED +3.4 OpenMPI 3.1.3 TensorRT 5.1.5	1.3.0 including OpenMPI 3.1.3 TensorRT 5.1.5	1.2.0 including OpenMPI 3.1.3 TensorRT 5.1.5	1.1.0 including OpenMPI 3.1.3 TensorRT 5.1.2 RC	1.0.0 including OpenMPI 3.1.3 TensorRT 5.1.2 RC	0.11.0 Beta including OpenMPI 3.1.3 TensorRT 5.0.2	0.10.0 Beta including OpenMPI 3.1.3 TensorRT 5.0.2
	TensorRT Inference Server	Docker image size: 6.12 GB		Docker image size: 6.15 GB		Docker image size: 8.26 GB	Docker image size: 7.73 GB	Docker image size: 7.73 GB	Docker image size: 7.15 GB	Docker image size: 7.15 GB	Docker image size: 7.02 GB	Docker image size: 5.22 GB	Docker image size: 5.33 GB	Docker image size: 4.42 GB	Docker image size: 4.17 GB
TensorFlow For Jetson		TensorFlow 1.15.0 and 2.0.0 for Jetson		TensorFlow 1.15.0 and 2.0.0 for Jetson		TensorFlow 1.14.0 for Jetson	TensorFlow 1.14.0 for Jetson	TensorFlow 1.14.0 for Jetson	TensorFlow 1.14.0 for Jetson		TensorFlow 1.13.1 for Jetson	TensorFlow 1.13.1 for Jetson	TensorFlow 1.13.1 for Jetson	TensorFlow 1.13.0-rc0 for Jetson	TensorFlow 1.12.0 for Jetson

18.xx Framework Containers Support Matrix

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 18.01 release of an image was released in January, 2018.

18.xx container images

Table 5. Software stack packaged with the 18.xx container images
	Container Image	18.12	18.11	18.10	18.09	18.08	18.07	18.06	18.05	18.04	18.03	18.02	18.01
Supported Platform	Host OS	DGX OS Server 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 4.0.4+ and 3.1.2+ (DGX Station)	DGX OS Server 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 4.0.4+ and 3.1.2+ (DGX Station) DGX Software Stack for Red Hat Enterprise Linux EL7-18.11 (DGX-1)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)	DGX OS Server 3.1.2+ and 2.1.1+ (DGX-1) 4.0.1+ (DGX-2) DGX OS Desktop 3.1.2+ (DGX Station)
Supported Platform	NVIDIA Driver	Release 18.12 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+. The CUDA driver's compatibility package only supports particular drivers (see footnote ¹).	Release 18.11 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+. The CUDA driver's compatibility package only supports particular drivers (see footnote ¹).	Release 18.10 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+. The CUDA driver's compatibility package only supports particular drivers (see footnote ¹).	Release 18.09 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+. The CUDA driver's compatibility package only supports particular drivers (see footnote ¹).	Ubuntu 16.04 NVIDIA Driver 384.xx+	Ubuntu 16.04 NVIDIA Driver 384.xx+	Ubuntu 16.04 NVIDIA Driver 384.xx+	Ubuntu 16.04 NVIDIA Driver 384.xx+	Ubuntu 16.04 NVIDIA Driver 384.xx+	Ubuntu 16.04 NVIDIA Driver 384.xx+	Ubuntu 16.04 NVIDIA Driver 384.xx+	Ubuntu 16.04 NVIDIA Driver 384.xx+
Supported Hardware	GPU Model	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Turing Volta Pascal	Volta and Pascal	Volta and Pascal	Volta and Pascal	Volta and Pascal	Volta and Pascal	Volta and Pascal	Volta and Pascal	Volta and Pascal
Base Image	Container OS	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04	Ubuntu 16.04
	CUDA	10.0.130	10.0.130	10.0.130	10.0.130 includes: Support for DGX-2 Support for Turing Support for Jetson Xavier CUDA 10 compatibility package version 410.48⁶	9.0.176	9.0.176	9.0.176	9.0.176	9.0.176	9.0.176	9.0.176	9.0.176
	cuBLAS	10.0.130	10.0.130	10.0.130	10.0.130	9.0.425	9.0.425	9.0.333	9.0.333	9.0.333	9.0.333	9.0.282 Patch 2 and cuBLAS 9.0.234 Patch 1	9.0.282 Patch 2
	cuDNN	7.4.1	7.4.1	7.4.0	7.3.0	7.2.1	7.1.4	7.1.4	7.1.2	7.1.1	7.1.1	7.0.5	7.0.5
	NCCL	2.3.7	2.3.7	2.3.6	2.3.4	2.2.13	2.2.13	2.2.13	2.1.15	2.1.15	2.1.2	2.1.2	2.1.2
NVIDIA Optimized Frameworks	NVCaffe	0.17.2 including Python 2.7 OpenMPI 3.1.2 TensorRT 5.0.2	0.17.1 including Python 2.7 OpenMPI 3.1.2 TensorRT 5.0.2	0.17.1 including Python 2.7 OpenMPI 3.1.2 TensorRT 5.0.0 RC	0.17.1 including Python 2.7 OpenMPI 2.0 TensorRT 5.0.0 RC	0.17.1 including Python 2.7 OpenMPI 2.0	0.17.1 and Python 2.7	0.17.0 and Python 2.7	0.17.0 and Python 2.7	0.17.0 and Python 2.7	0.16.6 and Python 2.7	0.16.5 and Python 2.7	0.16.5 and Python 2.7
	NVCaffe	Docker image size: 3.41 GB	Docker image size: 3.41 GB	Docker image size: 3.41 GB	Docker image size: 3.40 GB	Docker image size: 3.37 GB	Docker image size: 4.29 GB	0.17.0 and Python 2.7	0.17.0 and Python 2.7	0.17.0 and Python 2.7	0.16.6 and Python 2.7	0.16.5 and Python 2.7	0.16.5 and Python 2.7
	Caffe2					0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3
	Caffe2					Docker image size: 3.02 GB	Docker image size: 2.94 GB	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3	0.8.1 including Python 2.7 or Python 3.5 OpenMPI 1.10.3
	DIGITS	6.1.1 including Python 2.7 OpenMPI 3.1.2 NVCaffe 0.17.2 TensorFlow 1.12.0 TensorRT 5.0.2	6.1.1 including Python 2.7 OpenMPI 3.1.2 NVCaffe 0.17.1 TensorFlow 1.12.0-rc2 TensorRT 5.0.2	6.1.1 including Python 2.7 OpenMPI 3.1.2 NVCaffe 0.17.1 TensorFlow 1.10.0 TensorRT 5.0.0 RC	6.1.1 including Python 2.7 NVCaffe 0.17.1 TensorFlow 1.10.0 TensorRT 5.0.0 RC	6.1.1 including Python 2.7 NVCaffe 0.17.1 TensorFlow 1.9.0 Torch7	6.1.1 including Python 2.7 NVCaffe 0.17.1 TensorFlow 1.8.0 Torch7	6.1.1 including Python 2.7 NVCaffe 0.17.0 TensorFlow 1.8.0 Torch7	6.1.1 including Python 2.7 NVCaffe 0.17.0 TensorFlow 1.7.0 Torch7	6.1.1 including Python 2.7 NVCaffe 0.17.0 TensorFlow 1.7.0 Torch7	6.1.0 including Python 2.7 NVCaffe 0.16.6 TensorFlow 1.4.0 Torch7	6.1.0 including Python 2.7 NVCaffe 0.16.5 TensorFlow 1.4.0 Torch7	6.0.0 including Python 2.7 NVCaffe 0.16.5 TensorFlow 1.4.0 Torch7
	DIGITS	TensorFlow Docker image size: 5.03 GB Caffe Docker image size: 3.56 GB	TensorFlow Docker image size: 5.03 GB Caffe Docker image size: 3.56 GB	Docker image size: 6.17 GB	Docker image size: 5.33 GB	Docker image size: 6.20 GB	Docker image size: 7.16 GB
	Microsoft Cognitive Toolkit					2.5 including Python 3.6 OpenMPI 3.0.0	2.5 including Python 3.6 OpenMPI 3.0.0	2.5 including Python 3.6 OpenMPI 3.0.0	2.5 including Python 3.6 OpenMPI 3.0.0	2.4 including Python 3.6 OpenMPI 3.0.0	2.4 including Python 3.6 OpenMPI 3.0.0	2.3.1 including Python 3.4 OpenMPI 3.0.0	2.3.1 including Python 3.4 OpenMPI 3.0.0
	Microsoft Cognitive Toolkit					Docker image size: 6.17 GB	Docker image size: 6.13 GB	2.5 including Python 3.6 OpenMPI 3.0.0	2.5 including Python 3.6 OpenMPI 3.0.0	2.4 including Python 3.6 OpenMPI 3.0.0	2.4 including Python 3.6 OpenMPI 3.0.0	2.3.1 including Python 3.4 OpenMPI 3.0.0	2.3.1 including Python 3.4 OpenMPI 3.0.0
	NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet	1.3.1 including Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.28 OpenMPI 3.1.2 Horovod 0.15.1 TensorRT 5.0.2 DALI 0.5 Beta	1.3.0 including Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.28 OpenMPI 3.1.2 Horovod 0.15.1 TensorRT 5.0.2 DALI 0.4.1 Beta	1.3.0 including Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.28 OpenMPI 3.1.2 TensorRT 5.0.0 RC DALI 0.4 Beta	1.3.0 including Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.28 TensorRT 5.0.0 RC DALI 0.2 Beta	1.2.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.28 TensorRT 4.0.1 DALI 0.1.2 Beta	1.2.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.23 TensorRT 4.0.1 DALI 0.1.1 Beta	1.2.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.22 TensorRT 4.0.1	1.1.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.13	1.1.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.18.1	1.1.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.17.4	1.0.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.17.0	1.0.0 including Python 2.7 or Python 3.5 ONNX exporter 0.1 Amazon Labs Sockeye sequence-to-sequence framework 1.16.2
		Docker image size: 3.69 GB	Docker image size: 3.69 GB	Docker image size: 3.68 GB	Docker image size: 3.58 GB	Docker image size: 4.09 GB	Docker image size: 3.93 GB
	PyTorch	0.4.1+ including Python 3.6 Caffe2 APEx OpenMPI 3.1.2 DALI 0.5 Beta Tensor Core Optimized Examples: ResNet50 v1.5 GNMT v2 TensorRT 5.0.2	0.4.1+ including Python 3.6 Caffe2 APEx OpenMPI 3.1.2 DALI 0.4.1 Beta Tensor Core Optimized Examples: ResNet50 v1.5 GNMT v2 TensorRT 5.0.2	0.4.1+ including Python 3.6 Caffe2 APEx OpenMPI 3.1.2 DALI 0.4 Beta Tensor Core Optimized Examples: ResNet50 v1.5 GNMT v2 TensorRT 5.0.0 RC	0.4.1+ including Python 3.6 Caffe2 APEx DALI 0.2 Beta Tensor Core Optimized Examples: ResNet50 v1.5 GNMT v2 TensorRT 5.0.0 RC	0.4.1 including Python 3.6 Caffe2 0.8.1 APEx DALI 0.1.2 Beta Tensor Core Optimized Examples: GNMT v2	0.4.0 including Python 3.6 Caffe2 0.8.1 APEx DALI 0.1.1 Beta	0.4.0 including Python 3.6 Caffe2 0.8.1 APEx	0.4.0 including Python 3.6 Caffe2 0.8.1 APEx	0.3.1 and Python 3.6	0.3.0 and Python 3.6	0.3.0 and Python 3.6	0.3.0 and Python 3.6
	PyTorch	Docker image size: 6.08 GB	Docker image size: 6.08 GB	Docker image size: 6.00 GB	Docker image size: 5.89 GB	Docker image size: 5.64 GB	Docker image size: 5.67 GB	0.4.0 including Python 3.6 Caffe2 0.8.1 APEx	0.4.0 including Python 3.6 Caffe2 0.8.1 APEx	0.3.1 and Python 3.6	0.3.0 and Python 3.6	0.3.0 and Python 3.6	0.3.0 and Python 3.6
	TensorFlow	1.12.0 including Python 2.7 or Python 3.5 Horovod 0.15.1 OpenMPI 3.1.2 TensorBoard 1.12.0 MLNX_OFED 3.4 OpenSeq2Seq v18.12 TensorRT 5.0.2 DALI 0.5 Beta	1.12.0-rc2 including Python 2.7 or Python 3.5 Horovod 0.15.1 OpenMPI 3.1.2 TensorBoard 1.12.0 MLNX_OFED 3.4 OpenSeq2Seq v18.11 TensorRT 5.0.2 DALI 0.4.1 Beta	1.10.0 including Python 2.7 or Python 3.5 Horovod 0.13.10 OpenMPI 3.1.2 TensorBoard 1.10.0 MLNX_OFED 3.4 OpenSeq2Seq v18.10 TensorRT 5.0.0 RC DALI 0.4 Beta	1.10.0 including Python 2.7 or Python 3.5 Horovod 0.13.10 OpenMPI 3.0.0 TensorBoard 1.10.0 MLNX_OFED 3.4 OpenSeq2Seq v18.09 TensorRT 5.0.0 RC DALI 0.2 Beta	1.9.0 including Python 2.7 or Python 3.5 Horovod 0.12.1 OpenMPI 3.0.0 TensorBoard 1.9.0 MLNX_OFED 3.4 OpenSeq2Seq v0.5 TensorRT 4.0.1 DALI 0.1.2 Beta	1.8.0 including Python 2.7 or Python 3.5 Horovod 0.12.1 OpenMPI 3.0.0 TensorBoard 1.8.0 MLNX_OFED 3.4 OpenSeq2Seq v0.4 TensorRT 4.0.1 DALI 0.1.1 Beta	1.8.0 including Python 2.7 or Python 3.5 Horovod 0.12.1 OpenMPI 3.0.0 TensorBoard 1.8.0 MLNX_OFED 3.4 OpenSeq2Seq v0.2 TensorRT 4.0.1	1.7.0 including Python 2.7 or Python 3.5 Horovod 0.12.1 OpenMPI 3.0.0 TensorBoard 1.7.0 MLNX_OFED 3.4 OpenSeq2Seq v0.2 TensorRT 3.0.4	1.7.0 including Python 2.7 or Python 3.5 Horovod 0.11.3 OpenMPI 3.0.0 TensorBoard 0.4.0-rc1 MLNX_OFED 3.4	1.4.0 including Python 2.7 or Python 3.5 Horovod 0.11.3 OpenMPI 3.0.0 TensorBoard 0.4.0-rc1	1.4.0 including Python 2.7 or Python 3.5 Horovod 0.11.2	1.4.0 including Python 2.7 or Python 3.5 Horovod 0.11.2
	TensorFlow	Docker image size: 4.64 GB	Docker image size: 4.64 GB	Docker image size: 4.57 GB	Docker image size: 3.75 GB	Docker image size: 3.40 GB	Docker image size: 3.34 GB					1.4.0 including Python 2.7 or Python 3.5 Horovod 0.11.2	1.4.0 including Python 2.7 or Python 3.5 Horovod 0.11.2
	TensorFlow For Jetson	TensorFlow 1.12.0 for Jetson	TensorFlow 1.12.0-rc2 for Jetson
	TensorRT	TensorRT 5.0.2 including: Python 2.7 or Python 3.5 OpenMPI 3.1.2	TensorRT 5.0.2 including: Python 2.7 or Python 3.5 OpenMPI 3.1.2	TensorRT 5.0.0 RC including: Python 2.7 or Python 3.5 OpenMPI 3.1.2	TensorRT 5.0.0 RC including Python 2.7 or Python 3.5	4.0.1 and Python 2.7 or Python 3.5	4.0.1 and Python 2.7 or Python 3.5	4.0.1 and Python 2.7 or Python 3.5	3.0.4 and Python 2.7	3.0.4 and Python 2.7	3.0.4 and Python 2.7	3.0.4 and Python 2.7	3.0.1 and Python 2.7
	TensorRT	Docker image size: 3.00 GB	Docker image size: 3.00 GB	Docker image size: 2.99 GB	Docker image size: 2.98 GB	Docker image size: 2.56 GB	Docker image size: 2.61 GB	4.0.1 and Python 2.7 or Python 3.5	3.0.4 and Python 2.7	3.0.4 and Python 2.7	3.0.4 and Python 2.7	3.0.4 and Python 2.7	3.0.1 and Python 2.7
	TensorRT Inference Server	0.9.0 Beta including Python 3.5 OpenMPI 3.1.2 TensorRT 5.0.2	0.8.0 Beta including Python 3.5 OpenMPI 3.1.2 TensorRT 5.0.2	0.7.0 Beta including Python 3.5 OpenMPI 3.1.2 TensorRT 5.0.0 RC	0.6.0 Beta including Python 3.5 OpenMPI 2.0 TensorRT 5.0.0 RC	0.5.0 Beta including Python 2.7 or Python 3.5 TensorRT 4.0.1	0.4.0 Beta including Python 2.7 or Python 3.5 TensorRT 4.0.1	0.3.0 Beta including Python 2.7 or Python 3.5 TensorRT 4.0.1	0.2.0 Beta including Python 2.7 or Python 3.5 TensorRT 3.0.4	0.1.0 Beta
	TensorRT Inference Server	Docker image size: 4.17 GB	Docker image size: 4.17 GB	Docker image size: 4.15 GB	Docker image size: 4.42 GB	Docker image size: 2.37 GB	Docker image size: 2.47 GB			0.1.0 Beta
	Theano					1.0.2 and Python 2.7	1.0.2 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7
	Theano					Docker image size: 3.70 GB	Docker image size: 3.74 GB	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7	1.0.1 and Python 2.7
	Torch					7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7
	Torch					Docker image size: 3.06 GB	Docker image size: 3 GB	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7	7 and Python 2.7

17.xx Framework Containers Support Matrix

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 17.01 release of an image was released in January, 2017.

17.xx container images

Table 6. Software stack packaged with the 17.xx container images
	Container Image	17.12	17.11	17.10	17.09	17.07	17.06	17.05	17.04	17.03	17.02	17.01
Supported Platform	DGX OS	3.1.2+ and 2.1.1+	3.1.2+ and 2.1.1+	3.1.2+ and 2.1.1+	3.1.2+ and 2.1.1+	2.x+ and 1.x+	2.x+ and 1.x+	2.x+ and 1.x+	2.x+ and 1.x+	2.x+ and 1.x+	2.x+ and 1.x+	2.x+ and 1.x+
Supported Platform	NVIDIA Driver	384	384	384	384
Base Image	Ubuntu	16.04	16.04	16.04	16.04	16.04	16.04	16.04	16.04	16.04	14.04	14.04
	CUDA	9.0.176	9.0.176	9.0	9.0	8.0.61.2	8.0.61	8.0.61	8.0.61	8.0.61	8.0.61	8.0.54
	cuBLAS	9.0.234	9.0.234			patch 2
	cuDNN	7.0.5	7.0.4	7.0.3	7.0.2	6.0.21	6.0.21	6.0.21	6.0.20	6.0.20	6.0.13	6.0.10
	NCCL	2.1.2	2.1.2	2.0.5	2.0.5	2.0.3	1.6.1	1.6.1	1.6.1	1.6.1	1.6.1	1.6.1
NVIDIA Optimized Frameworks	NVCaffe	0.16.4	0.16.4	0.16.4	0.16.4	0.16	0.16	0.16	0.16	0.16	0.16	0.16
	Caffe2	0.8.1 and OpenMPI 1.10.3	0.8.1 and OpenMPI 1.10.3	0.8.1 and OpenMPI 1.10.3	0.8.1 and OpenMPI 1.10.3	0.7.0 and OpenMPI 1.10.3	0.7.0 and OpenMPI 1.10.3	0.5.0+ and OpenMPI 1.10.3	0.5.0+ and OpenMPI 1.10.3
	DIGITS	6.0.0 including NVCaffe 0.16.4 TensorFlow 1.4.0 Torch7	6.0.0 including NVCaffe 0.16.4 TensorFlow 1.3.0 Torch7	6.0.0 including NVCaffe 0.16.4 TensorFlow 1.3.0 Torch7	6.0.0 including NVCaffe 0.16.4 TensorFlow 1.3.0 Torch7	6.0.0 including NVCaffe 0.16 Torch7	5.0 including NVCaffe 0.16 Torch7	5.0 including NVCaffe 0.16 Torch7	5.0 including NVCaffe 0.16 Torch7	5.0 including NVCaffe 0.16 Torch7	5.0 including NVCaffe 0.16 Torch7	5.0 including NVCaffe 0.16 Torch7
	Microsoft Cognitive Toolkit	2.2 and OpenMPI 3.0.0	2.2 and OpenMPI 3.0.0	2.2	2.1	2.0	2.0	2.0.rc2	2.0.beta15.0	2.0.beta12.0	2.0.beta9.0	2.0.beta5.0
	NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet	1.0.0	0.12.0	0.11.0	0.11.0.rc3	0.10.0	0.10.0	0.9.3a+	0.9.3a+	0.9.3
	PyTorch	0.2.0	0.2.0	0.2.0	0.2.0	0.1.12	0.1.12	0.1.12	0.1.10
	TensorFlow	1.4.0	1.3.0	1.3.0	1.3.0	1.2.1	1.1.0	1.0.1	1.0.1	1.0.0	0.12.1	0.12.0
	TensorRT	3.0.1
	Theano	1.0.0rc1	1.0.0rc1	0.10beta3	0.10beta1	0.9.0	0.9.0	0.9.0	0.9.0	0.9.0rc3	0.8.0	0.8.0
	Torch	7	7	7	7	7	7	7	7	7	7	7

16.xx Framework Containers Support Matrix

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 16.12 release of an image was released in December, 2016.

16.xx container images

Table 7. Software stack packaged with the 16.xx container images
	Container Image	16.12
Supported Platform	DGX OS	2.x+ and 1.x+
Supported Platform	NVIDIA Driver
Base Image	Ubuntu	14.04
	CUDA	8.0.54
	cuBLAS
	cuDNN	6.0.5
	NCCL	1.6.1
NVIDIA Optimized Frameworks	NVCaffe	0.16
	Caffe2
	DIGITS	5.0 including NVCaffe 0.16 Torch7
	Microsoft Cognitive Toolkit	2.0.beta5.0
	NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet
	PyTorch
	TensorFlow	0.12.0
	TensorRT
	Theano	0.8.0
	Torch	7

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Copyright

¹ Starting with version 20.10, the Framework Containers require at least Mellanox-OFED driver version 4.9 installed on a system for NCCL multi-node applications (the Mellanox OFED driver 4.9 LTS is included in DGX OS 4.6). You might see a message if you are running a Framework Container on a system that does not have the required Mellanox OFED driver version installed. This message can be ignored if you don't plan to use NCCL for multi-node applications.

² NVIDIA acknowledges the wide use of CentOS and understands that it is a community-developed derivative of the NVIDIA supported Red Hat Enterprise Linux. Support for CentOS is available directly from the CentOS community. NVIDIA tests the Frameworks Containers primarily on Red Hat Linux but ensures that all NVIDIA provided software runs on tested CentOS versions and will try to identify and correct issues related to NVIDIA provided software.

³ For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades, CUDA Application Compatibility Support Matrix and NVIDIA CUDA and Drivers Support.

⁴ Versions 20.09 and earlier have Mellanox OFED 4.6 Mellanox verbs libraries and are able to work with the kernel mode drivers from Mellanox OFED 4.7 or earlier (for multinode).

⁵ We will stop supporting DGX OS 3.x in September 2019. Ensure you upgrade your DGX systems to DGX OS Server version 4.1 or greater or DGX OS Desktop version 4.1 or greater to obtain security and feature updates.

⁶ The compatibility package ensures that Linux drivers R384 are compatible with Tesla GPUs.