Abstract

These support matrices provide an overview of the supported platforms, features, and hardware capabilities of the TensorRT APIs, parsers, and layers.

For previously released TensorRT documentation, refer to the TensorRT Archives.

1. Features for Platforms and Software

This section lists the supported NVIDIA® TensorRT™ features based on which platform and software.
Note:
  • Serialized engines are not portable across platforms.
  • If a serialized engine was created using the version-compatible flag, it could run with newer versions of TensorRT within the same major version.
  • If a serialized engine was created with hardware compatibility mode enabled, it can run on more than one kind of GPU architecture; the specifics depend on the hardware compatibility level used. Otherwise, serialized engines are not portable across devices.
  • Refer to the minimum compatible driver versions in the NVIDIA CUDA Release Notes for specific NVIDIA Driver versions.

2. Hardware and Precision

The following table lists NVIDIA hardware and the precision modes each hardware supports. TensorRT has been compiled to support all NVIDIA hardware with SM 7.5 or higher capability. The table also lists the availability of DLA on this hardware. Refer to the following tables for the specifics.
Table 2. Supported Hardware
CUDA Compute Capability Example Devices TF32 FP32 FP16 FP8 BF16 INT8 FP16 Tensor Cores INT8 Tensor Cores DLA
9.0

NVIDIA H100

NVIDIA GH200 480GB

Yes Yes Yes Yes Yes Yes Yes Yes No
8.9 NVIDIA L40S Yes Yes Yes Yes Yes Yes Yes Yes No
8.7 NVIDIA DRIVE AGX Orin™ Yes Yes Yes No No Yes Yes Yes Yes
8.6 NVIDIA A10 Yes Yes Yes No Yes Yes Yes Yes No
8.0 NVIDIA A100 Yes Yes Yes No Yes Yes Yes Yes No
7.5 NVIDIA T4 No Yes Yes No No Yes Yes Yes No

3. Compute Capability Per Platform

The section lists the supported computing capability based on the platform.
Table 3. Compute Capability per Platform
Platform Compute capability
Linux x86-64 7.5, 8.0, 8.629, 8.930, 9.031
Windows 10 x64 7.5, 8.0, 8.632, 8.933, 9.034
Ubuntu 24.04 SBSA 7.5, 8.0, 8.6, 9.0
NVIDIA JetPack AArch64 8.7

4. Software Versions Per Platform

The section lists the supported software versions based on platform.
Table 4. List of Supported Platforms per Software Version
Platform Compiler version Python version
Ubuntu 20.04 x86-64 gcc 8.3.1 3.8
Ubuntu 22.04 x86-64 gcc 8.3.1 3.10
Ubuntu 24.04 x86-64 gcc 8.3.1 3.12
Rocky Linux 8.9 x86-64 gcc 8.3.1 3.8
Rocky Linux 9.3 x86-64 gcc 8.3.1  
SLES 15 x86-64 gcc 8.3.1 N/A
  • Windows 10 x64
  • Windows 11 x64
  • Windows Server 2019 x64
  • Windows Server 2022 x64
MSVC 2019 v16.9.2 N/A
Ubuntu 24.04 SBSA gcc 8.4 3.12
NVIDIA JetPack AArch64 gcc 11.4 3.10
Note: The Python version listed in the table is the version supported by the Debian or RPM packages. Python versions 3.8, 3.9, 3.10, 3.11, and 3.12 are supported when using Python wheel files from the tar or zip packages.

5. ONNX Operator Support

The ONNX operator support list for TensorRT can be found here.

Notices

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1 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
2 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
3 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
4 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
5 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
6 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
7 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
8 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
9 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
10 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
11 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
12 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
13 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
14 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
15 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
16 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
17 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
18 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
19 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
20 These CUDA versions are supported using a single build, built with CUDA toolkit 12.6 update 2. It is compatible with all CUDA 12.x versions and only requires driver 525.x.
21 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
22 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
23 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
24 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
25 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
26 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
27 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
28 These CUDA versions are supported using a single build, built with CUDA toolkit 11.8. It is compatible with all CUDA 11.x versions and only requires driver 450.x.
29 Requires CUDA Toolkit 11.1 or newer.
30 Requires CUDA Toolkit 11.8 or newer.
31 Requires CUDA Toolkit 11.8 or newer.
32 Requires CUDA Toolkit 11.1 or newer.
33 Requires CUDA Toolkit 11.8 or newer.
34 Requires CUDA Toolkit 11.8 or newer.