Dynamo Support Matrix#

This document provides the support matrix for Dynamo, including hardware, software and build instructions.

See also: Release Artifacts for container images, wheels, Helm charts, and crates | Feature Matrix for backend feature support

Backend Dependencies#

The following table shows the backend framework versions included with each Dynamo release:

Dependency

main (ToT)

v0.8.1.post1

v0.8.1 (latest)

v0.8.0

v0.7.1

v0.7.0.post1

v0.7.0

vLLM

0.14.1

0.12.0

0.12.0

0.12.0

0.11.0

0.11.0

0.11.0

SGLang

0.5.8

0.5.6.post2

0.5.6.post2

0.5.6.post2

0.5.3.post4

0.5.3.post4

0.5.3.post4

TensorRT-LLM

1.2.0rc6.post2

1.2.0rc6.post2

1.2.0rc6.post1

1.2.0rc6.post1

1.2.0rc3

1.2.0rc3

1.2.0rc2

NIXL

0.9.0

0.8.0

0.8.0

0.8.0

0.8.0

0.8.0

0.8.0

main (ToT) reflects the current development branch. v0.8.1.post1 is a patch release for PyPI wheels and TRT-LLM container only (no GitHub release).

Important

Currently TensorRT-LLM does not support Python 3.11 so installation of the ai-dynamo[trtllm] Python wheel will fail.

Dynamo Version

SGLang

TensorRT-LLM

vLLM

Dynamo 0.8.1

CUDA 12.9, CUDA 13.0 (🧪)

CUDA 13.0

CUDA 12.9, CUDA 13.0 (🧪)

Dynamo 0.8.0

CUDA 12.9, CUDA 13.0 (🧪)

CUDA 13.0

CUDA 12.9, CUDA 13.0 (🧪)

Dynamo 0.7.1

CUDA 12.8

CUDA 13.0

CUDA 12.9

Dynamo 0.7.0

CUDA 12.9

CUDA 13.0

CUDA 12.8

Patch versions (e.g., v0.8.1.post1, v0.7.0.post1) have the same CUDA support as their base version.

For detailed artifact versions and NGC links (including container images, Python wheels, Helm charts, and Rust crates), see the Release Artifacts page.

Hardware Compatibility#

CPU Architecture

Status

x86_64

Supported

ARM64

Supported

Dynamo provides multi-arch container images supporting both AMD64 (x86_64) and ARM64 architectures. See Release Artifacts for available images.

GPU Compatibility#

If you are using a GPU, the following GPU models and architectures are supported:

GPU Architecture

Status

NVIDIA Blackwell Architecture

Supported

NVIDIA Hopper Architecture

Supported

NVIDIA Ada Lovelace Architecture

Supported

NVIDIA Ampere Architecture

Supported

Platform Architecture Compatibility#

Dynamo is compatible with the following platforms:

Operating System

Version

Architecture

Status

Ubuntu

22.04

x86_64

Supported

Ubuntu

24.04

x86_64

Supported

Ubuntu

24.04

ARM64

Supported

CentOS Stream

9

x86_64

Experimental

Wheels are built using a manylinux_2_28-compatible environment and validated on CentOS Stream 9 and Ubuntu (22.04, 24.04). Compatibility with other Linux distributions is expected but not officially verified.

Caution

KV Block Manager is supported only with Python 3.12. Python 3.12 support is currently limited to Ubuntu 24.04.

Software Compatibility#

CUDA and Driver Requirements#

Dynamo container images include CUDA toolkit libraries. The host machine must have a compatible NVIDIA GPU driver installed.

Dynamo Version

Backend

CUDA Toolkit

Min Driver (Linux)

Min Driver (Windows)

Notes

0.8.1

vLLM

12.9

575.xx+

576.xx+

13.0

580.xx+

581.xx+

Experimental

SGLang

12.9

575.xx+

576.xx+

13.0

580.xx+

581.xx+

Experimental

TensorRT-LLM

13.0

580.xx+

581.xx+

0.8.0

vLLM

12.9

575.xx+

576.xx+

13.0

580.xx+

581.xx+

Experimental

SGLang

12.9

575.xx+

576.xx+

13.0

580.xx+

581.xx+

Experimental

TensorRT-LLM

13.0

580.xx+

581.xx+

0.7.1

vLLM

12.9

575.xx+

576.xx+

SGLang

12.8

570.xx+

571.xx+

TensorRT-LLM

13.0

580.xx+

581.xx+

0.7.0

vLLM

12.8

570.xx+

571.xx+

SGLang

12.9

575.xx+

576.xx+

TensorRT-LLM

13.0

580.xx+

581.xx+

Experimental CUDA 13 images are not published for all versions. Check Release Artifacts for availability.

CUDA Compatibility Resources#

For detailed information on CUDA driver compatibility, forward compatibility, and troubleshooting:

For extended driver compatibility beyond the minimum versions listed above, consider using cuda-compat packages on the host. See Forward Compatibility for details.

Cloud Service Provider Compatibility#

AWS#

Host Operating System

Version

Architecture

Status

Amazon Linux

2023

x86_64

Supported

Caution

AL2023 TensorRT-LLM Limitation: There is a known issue with the TensorRT-LLM framework when running the AL2023 container locally with docker run --network host ... due to a bug in mpi4py. To avoid this issue, replace the --network host flag with more precise networking configuration by mapping only the necessary ports (e.g., 4222 for nats, 2379/2380 for etcd, 8000 for frontend).

Build Support#

For version-specific artifact details, installation commands, and release history, see Release Artifacts.

Dynamo currently provides build support in the following ways:

Once you’ve confirmed that your platform and architecture are compatible, you can install Dynamo by following the Local Quick Start in the README.