---
# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
title: Support Matrix
subtitle: Hardware, software, and build compatibility for Dynamo
---

**See also:** [Release Artifacts](release-artifacts.md) for container images, wheels, Helm charts, and crates | [Feature Matrix](feature-matrix.md) for backend feature support

## At a Glance

**Latest stable release:** [v0.9.0](https://github.com/ai-dynamo/dynamo/releases/tag/v0.9.0) -- SGLang `0.5.8` | TensorRT-LLM `1.3.0rc1` | vLLM `0.14.1` | NIXL `0.9.0`

| Requirement | Supported |
| :--- | :--- |
| **GPU** | NVIDIA Ampere, Ada Lovelace, Hopper, Blackwell |
| **OS** | Ubuntu 22.04, Ubuntu 24.04, CentOS Stream 9 (experimental) |
| **Arch** | x86_64, ARM64 (ARM64 requires Ubuntu 24.04) |
| **CUDA 12** | Container images for SGLang and vLLM (CUDA 12.9) |
| **CUDA 13** | Container images for TensorRT-LLM (CUDA 13.0); experimental for SGLang and vLLM in v0.8.x |

**On this page:** [Backend Dependencies](#backend-dependencies) | [CUDA and Drivers](#cuda-and-driver-requirements) | [Hardware](#hardware-compatibility) | [Platform](#platform-architecture-compatibility) | [Cloud](#cloud-service-provider-compatibility) | [Build Support](#build-support)

## Backend Dependencies

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

| **Dynamo** | **SGLang** | **TensorRT-LLM** | **vLLM** | **NIXL** |
| :--- | :--- | :--- | :--- | :--- |
| **main (ToT)** | `0.5.9` | `1.3.0rc5` | `0.16.0` | `0.10.1` |
| **v1.0.0** *(in progress)* | `0.5.9` | `1.3.0rc5` | `0.15.1` | `0.10.1` |
| **v0.9.1** *(in progress)* | `0.5.8` | `1.3.0rc3` | `0.14.1` | `0.9.0` |
| **v0.9.0** | `0.5.8` | `1.3.0rc1` | `0.14.1` | `0.9.0` |
| **v0.8.1.post3** | `0.5.6.post2` | `1.2.0rc6.post3` | `0.12.0` | `0.8.0` |
| **v0.8.1.post2** | `0.5.6.post2` | `1.2.0rc6.post2` | `0.12.0` | `0.8.0` |
| **v0.8.1.post1** | `0.5.6.post2` | `1.2.0rc6.post1` | `0.12.0` | `0.8.0` |
| **v0.8.1** | `0.5.6.post2` | `1.2.0rc6.post1` | `0.12.0` | `0.8.0` |
| **v0.8.0** | `0.5.6.post2` | `1.2.0rc6.post1` | `0.12.0` | `0.8.0` |
| **v0.7.1** | `0.5.4.post3` | `1.2.0rc3` | `0.11.0` | `0.8.0` |
| **v0.7.0.post1** | `0.5.4.post3` | `1.2.0rc3` | `0.11.0` | `0.8.0` |
| **v0.7.0** | `0.5.4.post3` | `1.2.0rc2` | `0.11.0` | `0.8.0` |
| **v0.6.1.post1** | `0.5.3.post2` | `1.1.0rc5` | `0.11.0` | `0.6.0` |
| **v0.6.1** | `0.5.3.post2` | `1.1.0rc5` | `0.11.0` | `0.6.0` |
| **v0.6.0** | `0.5.3.post2` | `1.1.0rc5` | `0.11.0` | `0.6.0` |

### Version Labels

- **main (ToT)** reflects the current development branch.
- Releases marked *(in progress)* or *(planned)* show target versions that may change before final release.

### Version Compatibility

- Backend versions listed are the only versions tested and supported for each release.
- TensorRT-LLM does not support Python 3.11; installation of the `ai-dynamo[trtllm]` wheel will fail on Python 3.11.

### 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 | Notes |
| :--- | :--- | :--- | :--- | :--- |
| **1.0.0** *(in progress)* | **SGLang** | 12.9 | 575.xx+ | |
| | | 13.0 | 580.xx+ | |
| | **TensorRT-LLM** | 13.1 | 580.xx+ | |
| | **vLLM** | 12.9 | 575.xx+ | |
| | | 13.0 | 580.xx+ | |
| **0.9.1** *(in progress)* | **SGLang** | 12.9 | 575.xx+ | |
| | **TensorRT-LLM** | 13.0 | 580.xx+ | |
| | **vLLM** | 12.9 | 575.xx+ | |
| **0.9.0** | **SGLang** | 12.9 | 575.xx+ | |
| | **TensorRT-LLM** | 13.0 | 580.xx+ | |
| | **vLLM** | 12.9 | 575.xx+ | |
| **0.8.1** | **SGLang** | 12.9 | 575.xx+ | |
| | | 13.0 | 580.xx+ | Experimental |
| | **TensorRT-LLM** | 13.0 | 580.xx+ | |
| | **vLLM** | 12.9 | 575.xx+ | |
| | | 13.0 | 580.xx+ | Experimental |
| **0.8.0** | **SGLang** | 12.9 | 575.xx+ | |
| | | 13.0 | 580.xx+ | Experimental |
| | **TensorRT-LLM** | 13.0 | 580.xx+ | |
| | **vLLM** | 12.9 | 575.xx+ | |
| | | 13.0 | 580.xx+ | Experimental |
| **0.7.1** | **SGLang** | 12.8 | 570.xx+ | |
| | **TensorRT-LLM** | 13.0 | 580.xx+ | |
| | **vLLM** | 12.9 | 575.xx+ | |
| **0.7.0** | **SGLang** | 12.9 | 575.xx+ | |
| | **TensorRT-LLM** | 13.0 | 580.xx+ | |
| | **vLLM** | 12.8 | 570.xx+ | |

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

Experimental CUDA 13 images are not published for all versions. Check [Release Artifacts](release-artifacts.md) for availability.

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

#### CUDA Compatibility Resources

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

- [CUDA Compatibility Overview](https://docs.nvidia.com/deploy/cuda-compatibility/)
- [Why CUDA Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/why-cuda-compatibility.html)
- [Minor Version Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/minor-version-compatibility.html)
- [Forward Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/forward-compatibility.html)
- [FAQ](https://docs.nvidia.com/deploy/cuda-compatibility/frequently-asked-questions.html)

For extended driver compatibility beyond the minimum versions listed above, consider using `cuda-compat` packages on the host. See [Forward Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/forward-compatibility.html) for details.

## 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](release-artifacts.md) 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.

## 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](https://github.com/mpi4py/mpi4py/discussions/491#discussioncomment-12660609) 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](release-artifacts.md).

**Dynamo** currently provides build support in the following ways:

- **Wheels**: We distribute Python wheels of Dynamo and KV Block Manager:
  - [ai-dynamo](https://pypi.org/project/ai-dynamo/)
  - [ai-dynamo-runtime](https://pypi.org/project/ai-dynamo-runtime/)
  - [kvbm](https://pypi.org/project/kvbm/) as a standalone implementation.

- **Dynamo Container Images**: We distribute multi-arch images (x86 & ARM64 compatible) on [NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/collections/ai-dynamo):
  - [Dynamo Frontend](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/dynamo-frontend) *(New in v0.8.0)*
  - [SGLang Runtime](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/sglang-runtime)
  - [SGLang Runtime (CUDA 13)](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/sglang-runtime-cu13)
  - [TensorRT-LLM Runtime](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/tensorrtllm-runtime)
  - [vLLM Runtime](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/vllm-runtime)
  - [vLLM Runtime (CUDA 13)](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/vllm-runtime-cu13)
  - [Kubernetes Operator](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/kubernetes-operator)

- **Helm Charts**: [NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/collections/ai-dynamo) hosts the helm charts supporting Kubernetes deployments of Dynamo:
  - [Dynamo Platform](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/helm-charts/dynamo-platform) (includes CRDs)
  - [Dynamo Graph](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/helm-charts/dynamo-graph)

- **Rust Crates**:
  - [dynamo-runtime](https://crates.io/crates/dynamo-runtime/)
  - [dynamo-llm](https://crates.io/crates/dynamo-llm/)
  - [dynamo-async-openai](https://crates.io/crates/dynamo-async-openai/)
  - [dynamo-parsers](https://crates.io/crates/dynamo-parsers/)
  - [dynamo-config](https://crates.io/crates/dynamo-config/) *(New in v0.8.0)*
  - [dynamo-memory](https://crates.io/crates/dynamo-memory/) *(New in v0.8.0)*

Once you've confirmed that your platform and architecture are compatible, you can install **Dynamo** by following the [Local Quick Start](https://github.com/ai-dynamo/dynamo/blob/main/README.md#local-quick-start) in the README.
