Use Google Gemini
The Google Gemini provider routes NemoClaw to Google’s OpenAI-compatible Chat Completions endpoint.
The sandbox continues to use the managed inference.local route.
Credential
Set GEMINI_API_KEY in the host shell before onboarding.
NemoClaw keeps the credential on the host and uses provider-aware validation during retries.
Model Choices
The onboarding wizard offers these curated model IDs.
gemini-3.6-flash.gemini-3.1-pro-preview.gemini-3.1-flash-lite-preview.gemini-3-flash-preview.gemini-2.5-pro.gemini-2.5-flash-lite.
The wizard selects gemini-3.6-flash by default.
Onboard
Run the onboarding wizard and select Google Gemini.
Select a model when the wizard prompts you. NemoClaw validates the selected provider and model before creating the sandbox.
Validation
NemoClaw validates Gemini inference through its OpenAI-compatible Chat Completions path.
When you enter a custom Gemini model ID, NemoClaw checks Google’s native model catalog and accepts IDs with or without the models/ prefix.
It skips the Responses API probe because Gemini does not support /v1/responses.
When NemoClaw reads the native Google model catalog, it keeps only models that support generateContent.
Embedding-only models are filtered out of the catalog, so they do not appear as onboarding choices.
Troubleshooting
Model validation can fail with these messages:
Could not validate model against https://generativelanguage.googleapis.com/v1beta/models: <reason>NemoClaw could not read the Google model catalog. The<reason>value identifies an authentication, network, response, or pagination failure. VerifyGEMINI_API_KEY, host access togenerativelanguage.googleapis.com, and the reported response.Model '<model>' is not available from Google Gemini. Checked https://generativelanguage.googleapis.com/v1beta/models.The catalog did not contain the model ID. This message also appears when the catalog omitsmodels, because NemoClaw treats the response as an empty catalog. Check the ID for typing errors. Custom IDs can include or omit themodels/prefix. Embedding-only models do not appear because they do not supportgenerateContent.Unexpected Gemini model catalog response: expected a top-level models arrayThe Google model catalog returned a non-nullmodelsvalue that is not an array. Retry the request, then inspect the Google service or proxy response if the error continues.Gemini model catalog pagination repeated page token '<token>'The catalog repeated anextPageToken, so NemoClaw stopped reading pages. Retry the request, then inspect the Google service or proxy response if the error continues.Gemini model catalog pagination exceeded <count> pagesThe catalog exhausted the 25-pageGEMINI_MODEL_CATALOG_MAX_PAGESlimit. Retry the request, then inspect the Google service or proxy response if the error continues.Onboard inference smoke check failed.The validation request failed. The output shows the provider, model, and API base URL. Compare these values with your configuration.Validation probe summary: Chat Completions API: HTTP 404.This result comes from Google’s OpenAI-compatible/v1beta/openai/chat/completionsruntime route, not the native/v1beta/modelscatalog. A model appearing in the native catalog does not prove that the runtime route can serve it. NemoClaw stops because the sandbox uses the Chat Completions route for inference. Retry the request, then verify that the same key and model can invoke Google’s OpenAI-compatible Chat Completions endpoint.
Related Topics
- Choose a Model compares the curated Gemini models by task fit.
- Understand Provider Validation describes provider validation behavior.