Dynamo Support Matrix

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

Hardware Compatibility

CPU Architecture	Status
x86_64	Supported
ARM64	Experimental

Warning

While x86_64 architecture is supported on systems with a minimum of 32 GB RAM and at least 4 CPU cores, the ARM64 support is experimental and may have limitations.

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	Experimental
CentOS Stream	9	x86_64	Experimental

Note

For Linux, the ARM64 support is experimental and may have limitations. Wheels are built using a manylinux_2_28-compatible environment and they have been validated on CentOS 9 and Ubuntu (22.04, 24.04).

Compatibility with other Linux distributions is expected but has not been officially verified yet.

Caution

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

Software Compatibility

Runtime Dependency

Python Package	Version	glibc version	CUDA Version
ai-dynamo	0.6.0	>=2.28
ai-dynamo-runtime	0.6.0	>=2.28 (Python 3.12 has known issues)
NIXL	0.6.0	>=2.27	>=11.8

Build Dependency

Build Dependency	Version
TensorRT-LLM	1.1.0rc5
NIXL	0.6.0
vLLM	0.10.1.1
SGLang	0.5.3rc0

Important

Specific versions of TensorRT-LLM supported by Dynamo are subject to change. Currently TensorRT-LLM does not support Python 3.11 so installation of the ai-dynamo[trtllm] will fail.

Cloud Service Provider Compatibility

AWS

Host Operating System	Version	Architecture	Status
Amazon Linux	2023	x86_64	Supported¹

Caution

¹ 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

Dynamo currently provides build support in the following ways:

Wheels: Pre-built Python wheels are only available for x86_64 Linux. No wheels are available for other platforms at this time.
Runtime Container Images: We distribute only AMD64 images of the runtime target on NGC for TensorRT-LLM, vLLM, and SGLang. Users must build the container image from source if they require an ARM64 image.
Deployment-supportive Images: NGC hosts the Dynamo kubernetes-operator to simplify deployments of Dynamo Graphs. It is currently provided as an AMD64 image only.
Helm Charts: NGC hosts the helm charts supporting Kubernetes deployments of Dynamo. Dynamo CRDs, Dynamo Platform, and Dynamo Graph are available.

Once you've confirmed that your platform and architecture are compatible, you can install Dynamo by following the instructions in the Quick Start Guide.

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