How much does Gemini 3.1 Flash Image (Nano Banana 2) cost per 1M tokens?

Google AI lists $0.5 / $3 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 3.1 Flash Image (Nano Banana 2) 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.

Can I switch to Gemini 3.1 Flash Image (Nano Banana 2) without changing my code?

Yes. odnoga exposes one OpenAI-compatible endpoint, so switching means sending "gemini-3.1-flash-image" as the model id — or changing it in the managed prompt version, with no application deploy.

How large is the Gemini 3.1 Flash Image (Nano Banana 2) context window?

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

Gemini 3.1 Flash Image (Nano Banana 2)

Gemini 3.1 Flash Image (Nano Banana 2) by Google AI: $0.5 input and $3 output per 1M tokens, 66K context. Call it through the odnoga LLM gateway.

ReasoningVision

Gemini 3.1 Flash Image (Nano Banana 2) 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. Its 66K-token context window sets how much input you can send in one request.

Specification and price

Vendor	Google AI
Model ID	gemini-3.1-flash-image
Context window	66K tokens
Max output	66K tokens
Capabilities	Reasoning, Vision

Your plan

Per 1M tokens	Vendor cost	Your price on Free+7%
Input	$0.5	$0.538
Output	$3	$3.23
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-3.1-flash-image",
    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 3.1 Flash Image (Nano Banana 2)

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.

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.
Agent loops that must call your functions — tool calling is not available here.
Pipelines that require guaranteed JSON — parse defensively or pick a model with enforced JSON.
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.
04Budget for output tokens: reasoning happens on the output side, so a short answer can still be an expensive call.
05Set 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)	$5.38
Output (2M tokens)	$6.45
Your cost per month on Free	$11.83

Vendor list cost $11.00 + odnoga margin $0.828 (+7%). Cached input or answer reuse lowers it; odnoga records both numbers per request.