Choose a Model | NVIDIA NemoClaw

Use the curated model choices as starter guidance when selecting a cloud model during onboarding. The provider catalog remains authoritative for context-window limits and current pricing. Runtime route validation determines current availability because catalog entries can outlive their backing endpoints.

Catalog Selection

During interactive NVIDIA Endpoints onboarding, NemoClaw loads NVIDIA’s public featured model catalog once per onboarding session and reports progress before displaying the model picker. OpenRouter uses the same catalog-backed picker flow and source catalog, with its own provider route and credential check. It does not apply NVIDIA Endpoints retirement filters and uses its own bundled fallback list, so the available choices can differ. NVIDIA Endpoints excludes NVIDIA-retired or unsafe choices and corrects known catalog lag before displaying the result.

If the catalog is unavailable, malformed, or contains no safe model IDs, the wizard warns you and uses its bundled fallback list. Nemotron 3 Super remains the shared default for OpenClaw and Hermes when it is present. LangChain Deep Agents Code uses Nemotron 3 Ultra as its NVIDIA Endpoints default. If an agent’s default is unavailable, the first live featured model becomes the interactive default.

When a saved NVIDIA Endpoints route uses a retired model, interactive onboarding asks you to choose a replacement. Non-interactive onboarding uses NEMOCLAW_MODEL when configured with a non-retired model, otherwise it uses the agent’s default model. This retirement recovery applies only to NVIDIA Endpoints. OpenRouter recovery does not apply NVIDIA Endpoints retirement filters.

If NEMOCLAW_MODEL contains a safe custom model ID that is absent from the live catalog, it does not replace the live menu default. Choose Other to use that value as the pre-filled manual entry. NemoClaw validates the manual entry against the selected provider before continuing. NemoClaw does not display or accept an unsafe value as the manual-entry prefill.

Model Task Fit

The relative labels compare models within the curated onboarding choices rather than across every model that a provider offers.

Model	Best for	Relative latency	Tool use	Context fit	Relative cost
`nvidia/nemotron-3-ultra-550b-a55b`	Quality-sensitive reasoning, careful synthesis, and complex reviews	Higher	Strong for complex tool plans	Large agent context	Higher
`nvidia/nemotron-3-super-120b-a12b`	Hosted agent work, multi-step planning, and tool-heavy shell workflows	Medium	Strong default for OpenClaw tool loops	Large agent context	Medium
`gpt-5.4`	General OpenAI-backed agent work and high-quality reasoning	Medium	Strong	Large agent context	Medium to high
`gpt-5.4-mini`	Latency-sensitive routine automation and repeated helper calls	Low	Good	Medium to large context	Low
`gpt-5.4-nano`	Classification, routing, extraction, and small helper tasks	Very low	Basic to good for simple tool loops	Medium context	Very low
`gpt-5.4-pro-2026-03-05`	Quality-first complex reasoning where latency and cost are secondary	Highest	Validate Responses API support before long tool loops	Large agent context	Highest
`claude-sonnet-4-6`	Balanced coding, writing, analysis, and multi-step tool work	Medium	Strong	Large agent context	Medium to high
`claude-haiku-4-5`	Fast summarization, routing, extraction, and lightweight assistant turns	Low	Good for simple tool loops	Medium to large context	Low
`claude-opus-4-6`	Deep analysis, careful writing, and quality-first planning	Higher	Strong	Large agent context	Higher
`gemini-3.1-pro-preview`	Large-context analysis, synthesis, and preview-feature evaluation	Medium to high	Good, with tool continuation validation for the selected route	Extensive context	Medium to high
`gemini-3.1-flash-lite-preview`	Low-cost extraction, classification, and simple helper calls	Low	Basic to good for simple tool loops	Medium to large context	Low
`gemini-3-flash-preview`	Fast general assistant tasks and preview-feature evaluation	Low	Good for simple tool loops	Large context	Low
`gemini-3.6-flash`	Gemini 3 agent work through managed Chat Completions	Refer to provider catalog	OpenClaw managed-route compatibility	Refer to provider catalog	Refer to provider pricing
`gemini-2.5-pro`	Large-context analysis, long-document synthesis, and complex reasoning	Medium to high	Good	Extensive context	Medium to high
`gemini-2.5-flash-lite`	Lowest-cost helper calls, extraction, and classification	Very low	Basic to good for simple tool loops	Medium to large context	Very low

Nemotron Deployment Choice

Nemotron models expose OpenAI-compatible APIs across the supported deployment surfaces. Choose the onboarding option that matches the host.

Nemotron host	Onboarding option
NVIDIA-hosted on `build.nvidia.com`	NVIDIA Endpoints
Self-hosted NIM container	Other OpenAI-compatible endpoint
Enterprise NVIDIA AI Enterprise gateway	Other OpenAI-compatible endpoint
vLLM, SGLang, or TRT-LLM serving Nemotron weights	Other OpenAI-compatible endpoint
Local NIM started by the wizard	Local NVIDIA NIM

Choose an Inference Provider compares the deployment routes.
Use NVIDIA Endpoints explains the hosted NVIDIA catalog flow.
Understand Provider Validation explains how NemoClaw checks a selected model.

Catalog Selection

Model Task Fit

Nemotron Deployment Choice

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