How much does Gemini Omni 1.1 Flash 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 1.1 Flash 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 1.1 Flash without changing my code?

Yes. odnoga exposes one OpenAI-compatible endpoint, so switching means sending "gemini-omni-1.1-flash" as the model id — or changing it in the managed prompt version, with no application deploy.

How large is the Gemini Omni 1.1 Flash context window?

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

Gemini Omni 1.1 Flash

Gemini Omni 1.1 Flash by Google AI: $1.50 input and $9 output per 1M tokens, 131K context. Call it through the odnoga LLM gateway.

ReasoningReads imagesTool callingJSON schemaStreamingWeb search

Gemini Omni 1.1 Flash is served by Google AI and called through odnoga on /v1/chat/completions, in the same OpenAI-compatible shape every other model on that endpoint uses. 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-1.1-flash
Context window	131K tokens
Max output	66K tokens
Served on	/v1/chat/completions
Capabilities	Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search

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-1.1-flash",
    messages: [{ role: "user", content: "Hello" }],
  }),
});

One endpoint, one key, one bill — /v1/chat/completions takes the same shape whichever vendor is behind it. Swap the model id and odnoga handles keys, routing, limits and cost accounting.

What Gemini Omni 1.1 Flash can do

Everything below is what the model itself supports. Ask for something it does not do and odnoga tells you before the request reaches the provider, instead of returning a worse answer.

Reasoning

Works through a problem step by step before answering, which costs more tokens and buys accuracy on hard tasks.

Reads images

Send a screenshot, a photo or a scan in the same message as your text.

Tool calling

The model can call functions you define and use what they return.

JSON mode

Answers with valid JSON instead of prose you would have to parse.

JSON schema

Answers in the exact shape you specify, so the response fits your types without a fallback path.

Streaming

Tokens arrive as they are produced, so your interface can answer immediately.

Web search

Can look something up rather than answer from training data alone. Billed per search.

Beyond text

Listens to audio

Takes recorded speech as input.

Watches video

Takes video as input and answers questions about what happens in it.

Finer control

Structured outputs · The provider guarantees the schema rather than merely aiming for it.

How to use Gemini Omni 1.1 Flash

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.

If Gemini Omni 1.1 Flash is not the one

Models that take the same kind of input, are priced the same way, and do the closest thing to what this one does. Not a quality ranking — odnoga does not benchmark models.

Model	Context	Input / 1M	Output / 1M	Capabilities
Gemini Omni 1.1 Flash	131K	$1.50	$9	Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search
Gemini Omni Flash Preview	131K	$1.50	$9	Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search
Gemini 3.5 Flash	1.0M	$1.50	$9	Reasoning, Reads images, Tool calling, JSON schema, Streaming, Web search, Prompt caching, Batch
Gemini Robotics ER 2	131K	$1	$5	Reasoning, Reads images, Tool calling, JSON schema, Streaming, Prompt caching, Batch

Questions

How much does Gemini Omni 1.1 Flash 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 1.1 Flash 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 1.1 Flash without changing my code?: Yes. odnoga exposes one OpenAI-compatible endpoint, so switching means sending "gemini-omni-1.1-flash" as the model id — or changing it in the managed prompt version, with no application deploy.
How large is the Gemini Omni 1.1 Flash context window?: 131K tokens of input, with up to 66K tokens of output per response.

All models · Pricing · Docs · Compare models in the evaluation lab

Where this model sits

ProviderGoogle Gemini CapabilityReasoning CapabilityVision CapabilityTool calling

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