Dynamo Support Matrix | NVIDIA Dynamo Documentation

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

See also: Feature Compatibility Matrix for backend-specific feature support (vLLM, TensorRT-LLM, SGLang).

Hardware Compatibility

CPU Architecture	Status
x86_64	Supported
ARM64	Supported

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 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.

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	0.8.1	>=2.28
ai-dynamo-runtime	0.8.1	>=2.28 (Python 3.12 has known issues)
NIXL	0.8.0	>=2.27	>=11.8

Build Dependency

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

Dependency	main (ToT)	v0.8.0	v0.7.1	v0.7.0.post1	v0.7.0
SGLang	0.5.7	0.5.6.post2	0.5.3.post4	0.5.3.post4	0.5.3.post4
TensorRT-LLM	1.2.0rc6.post1	1.2.0rc6.post1	1.2.0rc3	1.2.0rc3	1.2.0rc2
vLLM	0.13.0	0.12.0	0.11.0	0.11.0	0.11.0
NIXL	0.8.0	0.8.0	0.8.0	0.8.0	0.8.0

main (ToT) reflects the current development branch.

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CUDA Support by Framework

Dynamo Version	SGLang	TensorRT-LLM	vLLM
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

🧪 = Experimental

Cloud Service Provider Compatibility

AWS

Host Operating System	Version	Architecture	Status
Amazon Linux	2023	x86_64	Supported¹

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: We distribute Python wheels of Dynamo and KV Block Manager:
- ai-dynamo
- ai-dynamo-runtime
- New as of Dynamo v0.7.0: kvbm as a standalone implementation.
Dynamo Runtime Images: We distribute multi-arch images (x86 & ARM64 compatible) of the Dynamo Runtime for each of the LLM inference frameworks on NGC:
- SGLang
- TensorRT-LLM
- vLLM
Dynamo Kubernetes Operator Images: We distribute multi-arch images (x86 & ARM64 compatible) of the Dynamo Operator on NGC:
- kubernetes-operator to simplify deployments of Dynamo Graphs.
Helm Charts: NGC hosts the helm charts supporting Kubernetes deployments of Dynamo:
Rust Crates:

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