Skip to main content
Gemini 1.5 through 3.5 (chat and reasoning), plus Gemma open-weights and the full multimodal lineup — image, video, TTS, audio, embeddings — all routable through Verlon in whichever SDK you already use. No Google-specific SDK required.

Chat models

This table is auto-generated from the Verlon model registry on every sync — see the live registry for pricing, benchmarks, and deprecation dates.

Other modalities

  • audio — 5 models
  • embeddings — 3 models
  • image generation — 7 models
  • text-to-speech — 3 models
  • video generation — 3 models
Non-chat Gemini models are called through the OpenAI SDK using the same model IDs — Verlon mirrors /v1/embeddings, /v1/images/generations, and /v1/audio/speech as drop-in routes. Video generation is drop-in too: the openai package’s async Videos surface (videos.create() / retrieve() / downloadContent()) works against /v1/videos.

Quickstart

First time? Create a gate and grab an API key — the examples below need a GATE_ID and VERLON_API_KEY.
The fastest path — the official OpenAI SDK, pointed at Verlon:
Any chat model from the table above works — swap gemini-2.5-pro for gemini-3.5-flash, gemini-flash-latest, or any other ID.

SDK compatibility

Any SDK with a Verlon drop-in endpoint can reach every model on this page — today that’s the OpenAI SDK and the Anthropic SDK: point it at Verlon, reference a gate that routes here, and your code stays unchanged. The quickstart above is all it takes. Verlon also mirrors Gemini’s native API at /v1beta/models/..., so tooling that speaks the Gemini REST shape works unchanged too. The Verlon SDK isn’t needed for inference — its home is agent tracing, observability, and the model registry.

Streaming

What’s supported

Full support for stream: true in every supported SDK — identical semantics to the source SDK.
Fully supported. Verlon translates the tool-call shape between OpenAI / Anthropic / Gemini native formats.
Image inputs work with any vision-capable Gemini model — including the multimodal Gemini 2.5 Flash and Pro lines.
temperature, max_tokens, top_p, stop_sequences, and the rest are passed through and mapped to Gemini’s native fields.
Every response includes token usage plus Verlon’s cost field with per-call dollar amount.

How it works

  1. You send a request in your chosen SDK’s format
  2. Verlon receives — validates the gate, applies routing rules
  3. Verlon translates to Gemini’s native format and dispatches to Google’s API
  4. Google responds with the raw Gemini response
  5. Verlon normalizes back to your SDK’s expected shape (OpenAI, Anthropic, or Gemini-native)
  6. You receive a response in the format your code already handles, with an added cost field
Your existing code doesn’t know it’s talking to Gemini.

Errors

The error shape always matches the SDK you’re calling with. Through the OpenAI SDK it surfaces as a thrown APIError:

Full non-chat model list

Every non-chat Google model Verlon routes to, grouped by modality. Chat models are in the table near the top of this page.

Audio

Embeddings

Image generation

Text-to-speech

Video generation