Inference providers
You can reach these models through the Google AI API itself or through a third-party provider.
Write the canonical model name, such as
gemini-3.5-flash, everywhere in Guild. Guild maps it to each provider’s own model ID.
Models
Guild prices and recognizes these Gemini model IDs. A policy or preference can also name any other model your credential can reach.Set up Gemini
On a managed account, agents can use Gemini models without a credential, as long as Guild holds a managed key for Gemini. To use your own Gemini account instead, add a credential. Adding your first credential switches the whole account to bring your own key (BYOK).1
Open Models & providers
Click Access & setup in the left nav, then Models & providers. In an organization, only admins can open it.
2
Add a credential
Click Add API key and choose an inference provider from the table above.
3
Enter the provider's secret
Give the credential a Name and paste your provider’s API key. AWS Bedrock asks for an IAM role and region instead.
4
Choose Gemini
Under Models, check Gemini. Keep
gemini-3.5-flash as its default model or enter another from the list above. Then click Add Key.--models "gemini-*-flash" limits a policy to matching models:
Use it from an agent
Agent code never names a credential. Guild resolves the call against the workspace owner’s settings. To ask for Gemini explicitly, put it inllmPreferences:
gemini-3.1-pro-preview. The second falls back to the default model of the matching policy. Preferences are strict: if no credential or policy allows any of them, the call fails rather than using another publisher. See LLM preferences.
Notes
- Guild requests Gemini’s thoughts, so the session can show reasoning progress.
- Gemini accepts a narrower JSON Schema than other publishers. Guild rewrites tool and structured-output schemas to fit before it sends them.
- In traces, Gemini calls carry the provider name
gcp.gemini, following the OpenTelemetry GenAI conventions.
Related pages
- Models & providers for credentials, model policies, and the daily token limit
- LLMs for
task.llmand the unified LLM proxy - Usage for spend by model