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Gemini 3.1 Pro Preview benchmarks, pricing and specs

Gemini 3.1 Pro Preview is a Google model released on February 19, 2026 that takes text, image, audio and video input and produces text. Its price is not published and accepts up to 1,048,576 tokens of context. It scores 1487 Elo on Arena Text, #8 of 39 current models (Arena, measured October 8, 2026).

Context window
1.05M
Arena Text
1487 Elo · #8/39

Data verified October 12, 2026 · Dataset 2026-10-12

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Key facts

Provider
Google
Model family
Gemini 3.1
Release date
February 19, 2026
Status
Current
Access
API only
API model id
Not reported
Context window
1,048,576 tokens
Max output
65,536 tokens
Input
text, image, audio, video
Output
text
Task families
text, multimodal
Declared capabilities
reasoning, coding, agentic coding

Gemini 3.1 Pro Preview pricing

UnitPrice (USD)TierAppliesSource
1M input tokensNot reportedstandardCurrent
1M output tokensNot reportedstandardCurrent
1M input tokensNot reportedcachedCurrent
1M input tokens$2standard up to 200kCurrent
1M output tokens$12standard up to 200kCurrent
1M input tokens$0.20cached up to 200kCurrent
1M input tokens$4standard over 200kCurrent
1M output tokens$18standard over 200kCurrent
1M input tokens$0.40cached over 200kCurrent

Independent benchmark results

Scores come from independent evaluators that ran the model themselves, pinned to a dated snapshot. Rank is among current models in the same snapshot. Google's own launch figures are listed under strengths with the publisher named, because they are not measured the same way.

BenchmarkScoreRankMeasuredSource
Arena Text1487 Elo#8 of 39October 8, 2026Arena · 2026-10-12
GPQA Diamond94.4%#6 of 37October 12, 2026Epoch AI · 2026-10-12
FrontierMath Tiers 1-3 (v2)59.6%#26 of 37October 12, 2026Epoch AI · 2026-10-12
SimpleQA Verified73.5%#3 of 34October 12, 2026Epoch AI · 2026-10-12

Strengths, cautions and best uses

Strengths

  • Google documents multimodal inputs, thinking, code execution, and function calling for Gemini 3.1 Pro Preview

Cautions

  • This preview endpoint may change before becoming stable; production use should account for its published prompt-length price tiers

Best for

  • Multimodal reasoning and agentic coding evaluations

Alternatives to Gemini 3.1 Pro Preview

The closest current textmodels by price. The cheapest model that scores as well or better is listed first; failing that, the cheapest one within 3% of the benchmark's scale.

Compare Gemini 3.1 Pro Preview with

Other Gemini 3.1 models

Gemini 3.1 Pro Preview FAQ

What is the context window of Gemini 3.1 Pro Preview?

Gemini 3.1 Pro Preview accepts up to 1,048,576 tokens of context. It can return up to 65,536 tokens in one response. That ranks #10 of 44 current text models by context length.

How does Gemini 3.1 Pro Preview score on independent benchmarks?

Gemini 3.1 Pro Preview scores 1487 Elo on Arena Text, #8 of 39 current models (Arena, measured October 8, 2026), 94.4% on GPQA Diamond, #6 of 37 current models (Epoch AI, measured October 12, 2026) and 59.6% on FrontierMath Tiers 1-3 (v2), #26 of 37 current models (Epoch AI, measured October 12, 2026). These are independent evaluations, not Google's own launch figures.

Is Gemini 3.1 Pro Preview open source or API only?

Gemini 3.1 Pro Preview is available through Google's API only; its weights are not published.

What are the best alternatives to Gemini 3.1 Pro Preview?

The closest current alternatives by price and measured performance are GPT-5.4 (12 points lower on Arena Text, 1475 vs 1487), Grok 4.20 (15 points lower on Arena Text, 1472 vs 1487), GPT-5.5 (5 points lower on Arena Text, 1482 vs 1487) and Gemini 3 Flash Preview (14 points lower on Arena Text, 1473 vs 1487).

Sources

Cite this page

Van Data Team. "Gemini 3.1 Pro Preview Benchmarks, Pricing and Specs." AI Model Benchmark Dataset 2026-10-12. https://vandatateam.com/ai-model-benchmarks/gemini-3-1-pro-preview

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Production evaluation

Deciding whether Gemini 3.1 Pro Preview fits your workload?

Public benchmarks narrow the shortlist. We test the finalists on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • Evaluation cases and acceptance thresholds tied to real work
  • Model routing, fallbacks and cost controls