DocumentationThis 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).
If you are using a GPU, the following GPU models and architectures are supported:
Dynamo is compatible with the following platforms:
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.
The following table shows the dependency versions included with each Dynamo release:
main (ToT) reflects the current development branch.
🧪 = Experimental
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).
Dynamo currently provides build support in the following ways:
Wheels: We distribute Python wheels of Dynamo and KV Block Manager:
Dynamo Runtime Images: We distribute multi-arch images (x86 & ARM64 compatible) of the Dynamo Runtime for each of the LLM inference frameworks on NGC:
Dynamo Kubernetes Operator Images: We distribute multi-arch images (x86 & ARM64 compatible) of the Dynamo Operator on NGC:
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.
