How much does Gemini Omni Flash Preview cost per 1M tokens?

Google AI lists $1.50 / $9 per 1M input / output tokens in the odnoga catalog. Through odnoga you pay that vendor price plus your plan margin, and every request is recorded with both numbers.

What is Gemini Omni Flash Preview best for?

Multi-step problems where the answer has to be worked out: planning, debugging, data reconciliation, analysis with intermediate steps. Work that mixes images with text — screenshots, scanned documents, charts, product photos. Agents and workflows that call your own functions, because the model supports tool calling.

Can I switch to Gemini Omni Flash Preview without changing my code?

Yes. odnoga exposes one OpenAI-compatible endpoint, so switching means sending "gemini-omni-flash-preview" as the model id — or changing it in the managed prompt version, with no application deploy.

How large is the Gemini Omni Flash Preview context window?

131K tokens of input, with up to 66K tokens of output per response.

Gemini Omni Flash Preview

Gemini Omni Flash Preview by Google AI: $1.50 input and $9 output per 1M tokens, 131K context. Call it through the odnoga LLM gateway.

ReasoningVisionToolsJSON modeStreaming

Gemini Omni Flash Preview is served by Google AI and called through odnoga with the same OpenAI-compatible request shape as every other model in the catalog. It is a reasoning model, so it spends extra output tokens working through a problem before answering — budget for higher output cost on hard tasks. It accepts images alongside text. It supports tool and function calling. It can be forced to return structured JSON. Its 131K-token context window sets how much input you can send in one request.

Specification and price

Vendor	Google AI
Model ID	gemini-omni-flash-preview
Context window	131K tokens
Max output	66K tokens
Capabilities	Reasoning, Vision, Tools, JSON mode, Streaming

Your plan

Per 1M tokens	Vendor cost	Your price on Free+7%
Input	$1.50	$1.61
Output	$9	$9.68
Cached input	—	—

Vendor cost is the list price per million tokens as recorded in the odnoga catalog; your price applies your plan margin with the same formula that bills every request — see pricing. Pricing

Call it through odnoga

const res = await fetch("https://api.odnoga.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.ODNOGA_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "gemini-omni-flash-preview",
    messages: [{ role: "user", content: "Hello" }],
  }),
});

Same request shape for every vendor in the catalog — swap the model id and odnoga handles keys, routing, limits and cost accounting.

How to use Gemini Omni Flash Preview

Derived from the odnoga catalog record for this model.

Best for

Multi-step problems where the answer has to be worked out: planning, debugging, data reconciliation, analysis with intermediate steps.
Work that mixes images with text — screenshots, scanned documents, charts, product photos.
Agents and workflows that call your own functions, because the model supports tool calling.
Machine-readable output you can write straight into a database, using enforced JSON.
User-facing chat where partial output should appear while the model is still writing.

Not the right pick when

Simple, high-frequency calls — reasoning spends extra output tokens, so a non-reasoning model in the same catalog is usually cheaper and faster.
Anything where a wrong answer is costly without a human check — no model in the catalog removes that requirement.

Practical tips through odnoga

01Pin the model id in a managed prompt version, so a model swap is a version change you can compare and roll back, not an edit in application code.
02Compare it against 2–8 other models on the same frozen test cases in the evaluation laboratory before you make it the production default.
03For repeated identical deterministic calls, odnoga answer reuse returns the stored answer and bills no vendor tokens — turn it off for creative output.
04Ask for JSON through the response format rather than in the prompt text — the schema is enforced instead of suggested.
05Budget for output tokens: reasoning happens on the output side, so a short answer can still be an expensive call.
06Set a fallback model on the route so a vendor incident degrades quality instead of returning an error, and a per-tenant budget so one caller cannot spend the month.

What a month costs

1,000 calls a month, 10,000 input tokens and 2,000 output tokens each, at your Free price (vendor cost +7%):

Input (10M tokens)	$16.13
Output (2M tokens)	$19.35
Your cost per month on Free	$35.48

Vendor list cost $33.00 + odnoga margin $2.48 (+7%). Cached input or answer reuse lowers it; odnoga records both numbers per request.