# Gemini 3.1 Pro

Gemini 3.1 Pro is a language model from Google with a 1M-token context window. Provider list price is $2 per million input tokens and $12 per million output; on Allocate you pay $2.14 and $12.84 with the 7% transaction fee. It is a closed model served over API; the weights are not published.

## Pricing

| | Provider list | On Allocate |
| --- | --- | --- |
| Input, per M tokens | $2 | $2.14 |
| Output, per M tokens | $12 | $12.84 |

Token usage bills at the provider list price plus the 7% transaction fee. Prices checked 2026-07-08.

## Facts

| Field | Value |
| --- | --- |
| Lab | Google |
| Modality | Language |
| Context window | 1M tokens |
| License | Proprietary API |
| Open weights | No |
| Fine-tunable | No |
| Catalog id | google/gemini-3.1-pro |

## What a real workload costs

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each: 1,200M input and 350M output tokens. At list prices that is 1,200 × $2 + 350 × $12 = $6,600 a month. Billed on Allocate it is $7,062 with the 7% transaction fee.

## Where it fits

Google’s flagship reasoner: 1M tokens of context at $2 per million input and $12 out. The step up from Flash for judgment-heavy routes that still need the big window.

- Judgment-heavy workflows
- Long-context analysis
- Escalation tier above Flash

## Common questions

### How much does Gemini 3.1 Pro cost per million tokens?

Provider list price is $2 per million input tokens and $12 per million output tokens. On Allocate you pay list plus the 7% transaction fee: $2.14 in and $12.84 out.

### What context window does Gemini 3.1 Pro have?

1,000,000 tokens (1M). At roughly 0.75 words per token, that is about 750k words of English text per request.

### Can I fine-tune Gemini 3.1 Pro?

No. Gemini 3.1 Pro is a closed model served over API; the weights are not published. If you want a model you can train and own, start from an open-weights base in the catalog and fine-tune that.

### How do I call Gemini 3.1 Pro on Allocate?

Send google/gemini-3.1-pro in the model field of the OpenAI-compatible endpoint at api.allocate.network/v1, or point a route name (like prod/support-agent) at it so you can swap the model later without a deploy.

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[HTML page](https://allocate.network/models/google-gemini-3-1-pro) · [Machine-readable catalog](https://allocate.network/catalog.json)