InferenceChoose a Provider and Model

Choose an Inference Provider

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Choose a provider based on where the model runs, which API it exposes, and which credential you can supply. NemoClaw validates the provider and model before it creates the sandbox.

Provider Support

Use this status table to distinguish validated provider integrations from adapters whose behavior depends on the selected compatible implementation.

ProviderStatusEndpoint typeNotes
NVIDIA EndpointsTestedOpenAI-compatibleHosted models on integrate.api.nvidia.com
OpenRouterTestedOpenAI-compatibleFirst-class onboarding route for OpenClaw, Hermes, and LangChain Deep Agents Code. NemoClaw registers the openrouter-api provider through OpenShell’s openai profile with a host runtime adapter URL; host-side validation and runtime traffic send the default OpenRouter attribution headers.
OpenAITestedNative OpenAI-compatibleUses OpenAI model IDs
Other OpenAI-compatible endpointTested with limitationsCustom OpenAI-compatibleCustom base-URL adapter for servers that implement OpenAI-compatible /v1/chat/completions or /v1/responses. Behavior on OpenAI-compatible proxies, gateways, and self-hosted implementations may vary; this row claims the adapter, not the universe of compatible endpoints.
AnthropicTestedNative AnthropicUses anthropic-messages
Other Anthropic-compatible endpointTested with limitationsCustom Anthropic-compatibleAdapter path validated with AWS Bedrock (src/lib/onboard/bedrock-runtime.ts). Behavior on other Anthropic-compatible proxies and gateways may vary; this row claims the adapter, not the universe of compatible endpoints.
Google GeminiTestedOpenAI-compatibleUses Google’s OpenAI-compatible endpoint
Hermes ProviderHermes onlyOpenAI-compatible routeAvailable when onboarding Hermes Agent through nemohermes
Local OllamaTested with limitationsLocal Ollama APIAvailable when Ollama is installed or running on the host. Validated default models: qwen3.6:35b (high VRAM), nemotron-3-nano:30b (medium VRAM), qwen3.5:9b (low VRAM fallback).
Local NVIDIA NIMExperimentalLocal OpenAI-compatibleRequires NEMOCLAW_EXPERIMENTAL=1 and a NIM-capable NVIDIA GPU. Host must have the NVIDIA Container Toolkit installed and a CDI spec present (onboard asserts CDI presence with assertCdiNvidiaGpuSpecPresent, src/lib/onboard/fatal-runtime-preflight.ts). NIM images pull from nvcr.io and require NGC registry login. NemoClaw gates this path behind the experimental flag because it does not auto-select a NIM image for the host today. You must explicitly pick from the validated image list. On Linux arm64 DGX Spark and DGX Station hosts, onboarding warns that some NIM images may not publish a linux/arm64 manifest; the warning is advisory, and the selected image pull can still fail when the registry has no matching platform manifest. Managed vLLM has host-specific default models and is not gated on the same boxes. Validated images referenced in src/lib/inference/config.ts and nemoclaw/src/index.ts: nvidia/nemotron-3-super-120b-a12b (default cloud model), nvidia/nemotron-3-nano-30b-a3b, nvidia/llama-3.3-nemotron-super-49b-v1.5.
Local vLLM (already running)Tested with limitationsLocal OpenAI-compatibleAppears in the onboarding menu when NemoClaw detects a server already on localhost:8000. No flag required. Model is whatever the existing server serves.
Local vLLM (managed install/start)Tested with limitationsLocal OpenAI-compatibleAppears by default on DGX Spark and DGX Station. Generic Linux NVIDIA GPU hosts require NEMOCLAW_EXPERIMENTAL=1 or NEMOCLAW_PROVIDER=install-vllm. Host must have the NVIDIA Container Toolkit installed and a CDI spec present (onboard asserts CDI presence). NemoClaw pulls or starts the stable NGC vLLM container for each host profile. See src/lib/inference/vllm.ts:55,177 for the pins. DGX Spark and DGX Station use nvcr.io/nvidia/vllm:26.05.post1-py3; generic Linux NVIDIA GPU hosts use nvcr.io/nvidia/vllm:26.03.post1-py3. Validated defaults are listed in src/lib/inference/vllm-models.ts: DGX Spark uses nvidia/Qwen3.6-35B-A3B-NVFP4, DGX Station uses deepseek-ai/DeepSeek-V4-Flash, and Linux NVIDIA GPU uses nvidia/NVIDIA-Nemotron-3-Nano-4B-FP8. Image pulls require NGC registry login (docker login nvcr.io); onboard prompts for the NGC API key when authentication is missing.

Hosted Providers

Hosted providers use provider-managed endpoints and curated model choices.

ProviderAPI routeCredentialSetup guide
NVIDIA EndpointsOpenAI-compatible Chat CompletionsNVIDIA_INFERENCE_API_KEYUse NVIDIA Endpoints
OpenRouterOpenAI-compatible Chat CompletionsOPENROUTER_API_KEYUse OpenRouter
OpenAINative OpenAI-compatibleOPENAI_API_KEYUse OpenAI
AnthropicAnthropic MessagesANTHROPIC_API_KEYUse Anthropic
Google GeminiGoogle OpenAI-compatible Chat CompletionsGEMINI_API_KEYUse Google Gemini

Hermes onboarding also offers Hermes Provider, which uses the host OpenShell provider registered by NemoClaw.

Local Providers

Local providers run on the host and keep inference traffic on infrastructure that you manage.

ProviderWhen it appearsSetup guide
Local OllamaOllama is installed or running on the host.Use Ollama
Local vLLM already runningNemoClaw detects a server on localhost:8000.Set Up vLLM
Local vLLM managed installThe host matches a supported GPU profile and any required opt-in is present.Set Up vLLM
Local NVIDIA NIMA NIM-capable NVIDIA GPU is present and experimental setup is enabled.Set Up NVIDIA NIM

Compatible Endpoints

Use a compatible endpoint when you operate a server or gateway that implements a supported inference API.

Provider optionRequired APICredentialSetup guide
Other OpenAI-compatible endpoint/v1/chat/completions, with optional /v1/responses selectionCOMPATIBLE_API_KEYSet Up an OpenAI-Compatible Endpoint
Other Anthropic-compatible endpoint/v1/messages for supported agents or /v1/chat/completions for OpenAI-compatible-only agentsCOMPATIBLE_ANTHROPIC_API_KEYSet Up an Anthropic-Compatible Endpoint

Behavior can vary across compatible proxies, gateways, and self-hosted implementations. The documented support applies to the NemoClaw adapter rather than every compatible endpoint implementation.

Routed Inference

Use Model Router when you want a host-side router to select from a configured model pool. The router registers as an OpenAI-compatible provider while the sandbox remains on inference.local.

Next Step

After you select a provider class, Choose a Model to compare curated hosted models by task fit.