> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/gym/_mcp/server. # Configure Models Configure your model with the inference backend of your choice. NeMo Gym uses the [Responses API](https://developers.openai.com/api/reference/resources/responses/methods/create) as its native schema because it natively represents tool calls, multi-turn conversations, and structured outputs. NeMo Gym provides middleware to automatically convert other protocols, for example, Chat Completions, into Responses format. For training, use a backend that returns token IDs and log probabilities (marked with training below). ## Available Backends #### [OpenAI](/model-server/openai) Use OpenAI models. cloud #### [Azure OpenAI](/model-server/azure-openai) Use models hosted on Azure OpenAI deployments. cloud #### [Inference Providers](/model-server/inference-providers) Use hosted providers like Fireworks, Together.ai, OpenRouter, and more. cloud #### [vLLM](/model-server/vllm) Connect to a vLLM server you start and manage yourself. self-hosted training #### [Local vLLM](/model-server/local-vllm) Let NeMo Gym launch and manage the vLLM server for you. self-hosted gym-managed training #### [Local vLLM Proxy](/model-server/local-vllm-proxy) Serve multiple request-time configs (e.g. reasoning on/off) from one Local vLLM deployment. self-hosted gym-managed training ## Observe model calls #### [Model-call capture](/model-server/model-call-capture) Record per-rollout model requests, responses, token usage, latency, and correlation evidence. observability ## Docs - [OpenAI](https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/openai.md): Use OpenAI (or any endpoint that natively serves the Responses API) with no conversion - [Azure OpenAI](https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/azure-openai.md): Use models hosted on Azure OpenAI deployments - [Inference Providers](https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/inference-providers.md): Use hosted inference providers like Fireworks, Together.ai, OpenRouter, and more for eval workloads - [Model-call capture](https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/model-call-capture.md): Optional per-rollout model-call evidence for evaluation and debugging - [vLLM](https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/vllm.md): Wrapper for an existing, external vLLM server - [Local vLLM](https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/local-vllm.md): Gym-managed vLLM server deployment - [Local vLLM Proxy](https://docs.nvidia.com/nemo/gym/v0.5.1/model-server/local-vllm-proxy.md): Expose one Local vLLM deployment as multiple model servers