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Gemini 3.1 Pro Preview

Verified

Mastering complex multimodal tasks with an enormous context window.

GoogleMultimodalClosed
Vision
Model page
Updated 2026-06-14

About Gemini 3.1 Pro Preview

The model is built on a sophisticated architecture that unifies processing of multiple modalities. It leverages a vast context capacity to maintain coherence over extended inputs. This design enables seamless handling of mixed media content.

Its strengths lie in the ability to reason across different data formats simultaneously. The large context window allows for detailed analysis of lengthy documents or conversations paired with visual and auditory elements. Users benefit from its closed nature which ensures controlled access to cutting-edge features.

Typical usage includes content creation, data analysis, and interactive applications involving multiple media types. Developers integrate it for tasks like video summarization with textual queries or audio transcription followed by reasoning. It serves professionals needing robust multimodal AI without open-weight availability.

Capabilities

Long-context reasoning
Multimodal understanding
Video and audio analysis
Code generation
Document and file processing
Cross-modal reasoning

How Gemini 3.1 Pro Preview compares

Gemini 3.1 Pro Preview (striped bar) vs other multimodal on intelligence, speed and price.

Price

USD per 1M output tokens · Lower is better · Gemini 3.1 Pro Preview ranks #90 of 122

$10.0
GPT-5.1-Codex-Max
$10.0
GPT-5
$10.0
Gemini 2.5 Pro
$10.0
GPT-5.1 Chat
$10.0
GPT-5 Chat
$12.0
Gemini 3.1 Pro Preview Custom Tools
$12.0
Gemini 3.1 Pro Preview
$12.0
Google Gemini Pro Latest
$12.5
Nova Premier 1.0
$14.0
GPT-5.3-Codex
$14.0
GPT-5.2
$14.0
GPT-5.2-Codex
$14.0
GPT-5.2 Chat

Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).

Best for

Long document analysis

The 1048576-token context allows the model to ingest and reason over entire books, research collections, or multi-file codebases in a single pass.

Video and audio understanding

Multimodal capabilities enable direct analysis of video clips and audio tracks for summarization, event detection, and cross-modal question answering.

Complex code generation

Strong performance on long-context code tasks supports generating, refactoring, and debugging large projects that span many files and dependencies.

Strengths & limitations

Strengths

  • +Handles up to 1M token contexts
  • +Native support for audio, image, video, and text
  • +Strong integration of multiple modalities
  • +Effective for large-scale document analysis

Limitations

  • Preview model may show inconsistent outputs
  • High resource use with maximum context
  • Requires verification on complex tasks

Cost calculator

Estimate what Gemini 3.1 Pro Preview would cost for your usage.

$0.00800
per request
$80
estimated / month

Based on Gemini 3.1 Pro Preview's $2.00/1M input · $12.00/1M output. Estimate only — actual cost varies by provider and caching.

Quick start

OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.

JavaScript · openai
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://openrouter.ai/api/v1",
  apiKey: process.env.OPENROUTER_API_KEY,
});

const completion = await client.chat.completions.create({
  model: "google/gemini-3.1-pro-preview",
  messages: [{ role: "user", content: "Hello!" }],
});

console.log(completion.choices[0].message.content);

Model slug: google/gemini-3.1-pro-preview

Editor's verdict

Our take on Gemini 3.1 Pro Preview

Gemini 3.1 Pro Preview is Google's proprietary multimodal with a 1049K-token context window.

At $12.00 per 1M output tokens, it is premium-priced for its class.

It is available through Google's API and aggregators like OpenRouter.

Best suited to handles up to 1m token contexts and native support for audio, image, video, and text.

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Frequently asked questions

The model supports a context length of 1048576 tokens.

User reviews

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Other Gemini models

Sibling versions in the Gemini family from Google.

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