Linux / arm64
Linux / amd64
The Dynamo gpt-oss TensorRT-LLM runtime container is a specialized, Docker-based environment designed to run NVIDIA Dynamo with the TensorRT-LLM backend, specifically optimized for OpenAI Open Source. This container streamlines high-performance, distributed large language model (LLM) inference by packaging all required dependencies, runtime components, and optimizations. It ensures a consistent, production-ready environment for deploying and serving OpenAI-style models with maximum efficiency on NVIDIA GPUs.
Key Components
TensorRT-LLM Backend: TensorRT-LLM Backend: Leverages NVIDIA’s open-source TensorRT-LLM library for state-of-the-art LLM inference optimizations.
Dynamo Core Services: Provides HTTP API server, request routing, and distributed worker processes for scalable prefill and decode operations.
Distributed Coordination: Integrates with etcd and NATS for robust service discovery and messaging.
OpenAI-Compatible API: Exposes endpoints matching OpenAI’s API, enabling seamless integration with existing OpenAI-compatible clients and tools.
gpt-oss Model Support: Ensures compatibility and optimized performance.
For more information about Dynamo features, please refer to the Github repository
Select the Tags tab and locate the container image release that you want to run.
In the Pull Tag column, click the icon to copy the docker pull command.
Open a command prompt and paste the pull command. The pulling of the container image begins. Ensure the pull completes successfully before proceeding to the next step.
Start required services (etcd and NATS) using Docker Compose:
docker compose -f deploy/docker-compose.yml up -d
Run the container image and verify dynamo via:
dynamo --version
For more examples, please refer to the examples directory in the repository.
Please refer to the following support matrix to learn more about the current hardware & architecture support.
NVIDIA Dynamo is released under an open-source license, Apache-2.0, making it freely available for development, research, and deployment.
GitHub Issues: Dynamo GitHub Issues