Overview

The Dynamo Frontend container is a lightweight, framework-less image designed to deploy and run CPU-bound frontend components without requiring CUDA or backend engine dependencies (vLLM, SGLang, TensorRT-LLM). It enables flexible deployment topologies by separating the frontend from inference backends, and integrates with the Gateway API Inference Extension (GAIE) for Kubernetes-native request routing.\nQuick Links: Key Components | Release Info | Getting Started | Support

Key Components

OpenAI-Compatible Frontend: HTTP API server compatible with OpenAI's chat completions and completions endpoints, handling request preprocessing, validation, and response formatting.
Endpoint Picker (EPP): InferenceScheduler with routing, flow control, and request management for intelligent backend selection. Integrates with Gateway API Inference Extension (GAIE) for Kubernetes-native load balancing.
Request Router: Routes requests to appropriate backend workers based on prefix matching, load, and KV cache state.
Mock Workers: Test Dynamo components without GPU backends for development, CI/CD, and validation workflows.
Kubernetes-Native Infrastructure: Service discovery via EndpointSlices and transport-agnostic request plane (TCP default) enable deployment without etcd or NATS dependencies.\nFor more information about Dynamo frontend and GAIE, please refer to the GitHub repository and GAIE documentation.

Release Info

For the complete release history including architecture details, see the Release Artifacts page.\nPre-built containers are available for both x86_64 (AMD64) and ARM64 architectures.

Getting Started

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. Ensure the pull completes successfully.
Run the container:

\n\">

docker run -it nvcr.io/nvidia/ai-dynamo/dynamo-frontend:<version>\n

For next steps, including deployment options and examples, please refer to the Dynamo README.

Use Cases

Separated Frontend Deployment: Run frontend on CPU nodes while backends run on GPU nodes
Gateway API Integration: Use with GAIE for Kubernetes-native inference routing
Development & Testing: Test Dynamo pipelines with mock workers without GPU resources
CI/CD Validation: Validate configurations and routing logic in automated pipelines

Support Matrix

Please refer to the support matrix for detailed hardware and architecture support.

Related Containers

vLLM Runtime - vLLM inference backend
SGLang Runtime - SGLang inference backend
TensorRT-LLM Runtime - TensorRT-LLM inference backend
Kubernetes Operator - K8s deployment automation

License

NVIDIA Dynamo is released under the Apache-2.0 open-source license, making it freely available for development, research, and deployment.

Technical Support

Documentation: Dynamo Documentation
GAIE Guide: Gateway API Inference Extension
GitHub Issues: Dynamo GitHub Issues
Release Notes: GitHub Releases

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It enables flexible deployment topologies by separating the frontend from inference backends, and integrates with the Gateway API Inference Extension (GAIE) for Kubernetes-native request routing.\n**Quick Links:** [Key Components](#key-components) | [Release Info](#release-info) | [Getting Started](#getting-started) | [Support](#technical-support)\n## Key Components\n- **OpenAI-Compatible Frontend**: HTTP API server compatible with OpenAI's chat completions and completions endpoints, handling request preprocessing, validation, and response formatting.\n- **Endpoint Picker (EPP)**: InferenceScheduler with routing, flow control, and request management for intelligent backend selection. Integrates with Gateway API Inference Extension (GAIE) for Kubernetes-native load balancing.\n- **Request Router**: Routes requests to appropriate backend workers based on prefix matching, load, and KV cache state.\n- **Mock Workers**: Test Dynamo components without GPU backends for development, CI/CD, and validation workflows.\n- **Kubernetes-Native Infrastructure**: Service discovery via EndpointSlices and transport-agnostic request plane (TCP default) enable deployment without etcd or NATS dependencies.\nFor more information about Dynamo frontend and GAIE, please refer to the [GitHub repository](https://github.com/ai-dynamo/dynamo) and [GAIE documentation](https://github.com/ai-dynamo/dynamo/tree/main/deploy/inference-gateway).\n## Release Info\nFor the complete release history including architecture details, see the [Release Artifacts](https://docs.nvidia.com/dynamo/latest/getting-started/release-artifacts) page.\nPre-built containers are available for both x86_64 (AMD64) and ARM64 architectures.\n## Getting Started\n1. Select the **Tags** tab and locate the container image release that you want to run.\n2. In the **Pull Tag** column, click the icon to copy the docker pull command.\n3. Open a command prompt and paste the pull command. Ensure the pull completes successfully.\n4. Run the container:\n```shell\ndocker run -it nvcr.io/nvidia/ai-dynamo/dynamo-frontend:\n```\nFor next steps, including deployment options and examples, please refer to the [Dynamo README](https://github.com/ai-dynamo/dynamo#readme).\n## Use Cases\n- **Separated Frontend Deployment**: Run frontend on CPU nodes while backends run on GPU nodes\n- **Gateway API Integration**: Use with GAIE for Kubernetes-native inference routing\n- **Development & Testing**: Test Dynamo pipelines with mock workers without GPU resources\n- **CI/CD Validation**: Validate configurations and routing logic in automated pipelines\n## Support Matrix\nPlease refer to the [support matrix](https://docs.nvidia.com/dynamo/latest/getting-started/support-matrix) for detailed hardware and architecture support.\n## Related Containers\n- [vLLM Runtime](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/vllm-runtime) \\- vLLM inference backend\n- [SGLang Runtime](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/sglang-runtime) \\- SGLang inference backend\n- [TensorRT-LLM Runtime](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/tensorrtllm-runtime) \\- TensorRT-LLM inference backend\n- [Kubernetes Operator](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/containers/kubernetes-operator) \\- K8s deployment automation\n## License\nNVIDIA Dynamo is released under the Apache-2.0 open-source license, making it freely available for development, research, and deployment.\n## Technical Support\n- **Documentation**: [Dynamo Documentation](https://docs.nvidia.com/dynamo/latest/)\n- **GAIE Guide**: [Gateway API Inference Extension](https://github.com/ai-dynamo/dynamo/tree/main/deploy/inference-gateway)\n- **GitHub Issues**: [Dynamo GitHub Issues](https://github.com/ai-dynamo/dynamo/issues)\n- **Release Notes**: [GitHub Releases](https://github.com/ai-dynamo/dynamo/releases)","Dynamo 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As part of our bot management service, this cookie helps manage incoming traffic that matches criteria associated with bots.\nThis is a CloudFoundry cookie","OptanonConsent","nvid.nvidia.com","This cookie is set by the cookie compliance solution from OneTrust. It stores information about the categories of cookies the site uses and whether visitors have given or withdrawn consent for the use of each category. This enables site owners to prevent cookies in each category from being set in the users browser, when consent is not given. The cookie has a normal lifespan of one year, so that returning visitors to the site will have their preferences remembered. It contains no information that can identify the site visitor.","events.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","sessionid","This is a very generic cookie name that may have different purposes on different sites, but generally it will be some kind of anonymous session identifier.","_csrf","This cookie is used to prevent Cross-Site Request Forgery (CSRF) attacks, ensuring that each request made to the server is from the user's browser and is intentional.","enterprise-support.nvidia.com","Used to apply end-user cookie consent preferences set by our client-side utility.Custom- Short Duration. Unique ID of an Enquiry- used to validate access to case, and load exisiting data.\n","renderCtx","academicgrants.nvidia.com","Used to store site parameters in the session for reuse across requests by a single client for functionality and performance reasons.","ph_phc_yQgAEdJJkVpI24NdSRID2mor1x1leRpDoC9yZ9mfXal_posthog","The PostHog ph_phc_xxx cookie is a session cookie used for identifying and tracking visitors on websites, helping us understand user behavior and website performance.","This cookie is managed by AWS and is used for load balancing.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","This cookie is associated with Akamai and is used to differentiate between traffic from humans and bots.","OptanonAlertBoxClosed","docs.ngc.nvidia.com","This cookie is set by websites using certain versions of the cookie law compliance solution from OneTrust. It is set after visitors have seen a cookie information notice and in some cases only when they actively close the notice down. It enables the website not to show the message more than once to a user. The cookie has a normal lifespan of one year and contains no personal information.","nv_co","__uxq412__ses.88c1","investor.nvidia.com","learn.learn.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","bpazaws52gukakzc__ctrl0_ctl36_uccaptcha","bm_sv","store.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","_devzone_session","This cookie is likely used to maintain a user session on the website by the server. It is common for session identifiers to be used to keep users logged in and track their interaction with the site during a session.","_cs_c","The cookie is used by Content Square to save the user consent to be tracked.","bm_sz","This cookie is used by Akamai to optimize site performance and security. It is typically associated with the delivery of web content and services.","vcalliance.nvidia.com","ASP.NET_SessionId","General purpose platform session cookie, used by sites written with Microsoft .NET based technologies. 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