Skip to main content
This page covers Gemini through Google AI Studio API keys. For Gemini on Google Cloud’s Vertex AI, see the Google Vertex AI guide. By default, GoModel routes Gemini chat, Responses, embeddings, and image requests through Gemini’s native APIs (generateContent, batchEmbedContents, Imagen predict). Switch to the OpenAI-compatible endpoint when you need compatibility behavior the native adapter does not implement yet (notably remote image_url values).

​
Configure

Or in config.yaml:
USE_GOOGLE_GEMINI_NATIVE_API is still honored as a legacy global toggle when per-provider GEMINI_API_MODE is unset. Prefer GEMINI_API_MODE.
Native AI Studio mode can also materialize GoModel’s post-routing prompt-cache plans as five-minute Gemini cached-content objects. Reuse is scoped to the API key selected for the session; sessionless traffic with rotating keys skips object creation so a resource is never reused under the wrong credential. Vertex currently receives the original request without cached-content objects.

​
Base URLs

GoModel keeps separate internal bases for native Gemini and the OpenAI-compatible API:
  • native chat/models: https://generativelanguage.googleapis.com/v1beta
  • OpenAI-compatible: https://generativelanguage.googleapis.com/v1beta/openai
GEMINI_BASE_URL overrides them. When the value ends in /openai, GoModel uses it for the OpenAI-compatible client and derives the native base by stripping /openai. Files and batches always use the OpenAI-compatible surface; chat, embeddings, and images follow the API mode.

​
Embeddings

In native mode, embeddings are served through models/{model}:batchEmbedContents. dimensions maps to outputDimensionality and encoding_format: "base64" is honored. Gemini reports no embedding token usage on either API surface, so embedding responses carry zero token counts and the usage row is flagged with a cost-calculation caveat.

​
Image generation and edits

In native mode the OpenAI-compatible image endpoints work with Gemini image models (gemini-2.5-flash-image, …, via generateContent). Google retired Imagen from the AI Studio API in August 2026; Imagen is still served on Vertex AI. Image edits require native mode and a Gemini image model; masks are not supported. See the Images API provider notes for parameter mapping and pricing details.

​
Reasoning effort

In native mode, reasoning_effort (or reasoning.effort) is translated to Gemini’s thinkingConfig: Thinking cannot be turned off on Gemini 3, and Pro models plus 3.7 and 3.8 Flash reject minimal, so GoModel sends the lowest level those models accept instead of surfacing Google’s 400. An explicit extra_body.google.thinking_config is always forwarded unchanged.

​
Sampling parameters on Gemini 3

Google’s Gemini 3 migration guides say to remove temperature, top_p and top_k from every request because the models are tuned for their defaults, and list candidate_count as unsupported on Gemini 3.x. In native mode GoModel therefore drops those four fields for Gemini 3 and later (gemini-3-*, gemini-3.5-*, gemini-3.8-*, …) and still forwards them for Gemini 2.5, Gemma and other models. max_tokens, stop, penalties, response_format and thinking settings are unaffected.

​
Image input

For URL-hosted images in native mode, Google’s own examples fetch the URL first and send the bytes to generateContent.

​
Not yet integrated

  • Automatic fetching of remote image_url values in native mode.
  • Uploading remote images through the Gemini Files API before a chat request.

​
References

Last modified on September 2, 2026