Gemini 3.1 Pro
by Google DeepMind · United StatesGoogle's most recent Pro model, still served under a preview model ID. Past 200K-token prompts input costs double and output half as much again. Google computed its own GPQA and Terminal-Bench 2.0 figures rather than taking them from a leaderboard.
Specification
The numbers
- Maker
- Google DeepMind
- Released
- 2026-02
- Parameters
- Not reported
- Architecture
- Not reported
- Context window
- 1,048,576 tokens
- Max output
- 65,536 tokens
- Input
- Text, Image, Audio, Video
- Output
- Text
- Reasoning
- Yes
- Tool calling
- Yes
- Knowledge cutoff
- Not reported
- Licence
- Proprietary
- Availability
- Not reported
- Weights
- Not released
API model ID: gemini-3.1-pro-preview
Cost
Price per million tokens
- Input
- $2.00 / M tokens
- Output
- $12.00 / M tokens
- Blended 3:1
- $4.50
Standard first-party API rate, excluding batch discounts. Reasoning models bill thinking tokens as output, so cost per answer can far exceed the cost per token suggests.
Published scores
Benchmarks
Figures published by Google DeepMind or taken from a public leaderboard. Row last checked 2026-10.
| Category | Score | Rank |
|---|---|---|
| ReasoningGPQA Diamond | 94.3% | 4 of 99 reporting the same tests |
| MathsCompetition mathematics, graded on the final answer | Not reported | — |
| CodingSWE-bench Verified, SWE-bench Pro, Terminal-Bench 2.0, Terminal-Bench 2.1 | 68.4% | Only model reporting these |
| KnowledgeBreadth of factual recall under exam conditions | Not reported | — |
| MultimodalReading charts, diagrams and photographs | Not reported | — |
| Instruction followingObeying an exact, checkable format | Not reported | — |
| Human preferenceWhich answer people pick, blind | Not reported | — |
A category averages every benchmark in it that Gemini 3.1 Pro reports. The rank counts only models that report the same tests, so it never compares an average over three benchmarks against an average over one.
Every reported test
| MMLU-ProKnowledge | Not reported | No figure published |
|---|---|---|
| GPQA DiamondReasoning | Rank 4 of 99 models reporting | |
| AIME 2025Maths | Not reported | No figure published |
| MATH-500Maths | Not reported | No figure published |
| SWE-bench VerifiedCoding | Rank 3 of 41 models reporting | |
| SWE-bench ProCoding | Rank 14 of 14 models reporting | |
| Terminal-Bench 2.0Coding | Rank 2 of 5 models reporting | |
| Terminal-Bench 2.1Coding | Rank 10 of 12 models reporting | |
| Frontier-Bench v0.1Reasoning | Not reported | No figure published |
| Terminal-Bench 4.0Coding | Not reported | No figure published |
| LiveCodeBenchCoding | Not reported | No figure published |
| HumanEvalCoding | Not reported | No figure published |
| MMMUMultimodal | Not reported | No figure published |
| IFEvalInstruction following | Not reported | No figure published |
| LMArena EloHuman preference | Not reported | No figure published |
Where these numbers come from
Every score on this page is a published figure, taken from the model's own card, system card, technical report or release post, or from a public leaderboard. CorX Labs did not run these evaluations. Most are self-reported by the lab that built the model, which means they were produced under that lab's own choice of prompt, scaffold and number of attempts — so treat them as a starting point for a shortlist, not as a settled ranking.
A score someone other than the model's maker measured is marked Independent and names its measurer. Those are the stronger numbers on this page — an outside harness has no reason to flatter anyone — and there are not many of them.
Where a figure has not been published, the cell reads Not reported rather than an estimate. Nothing here is inferred, interpolated or guessed. Each model records the month its row was last checked. Full method and caveats.
Head to head
Gemini 3.1 Pro compared
Same maker
Other models from Google DeepMind
| Gemini 3.8 FlashGoogle DeepMind | Google DeepMind | 1M | $0.75 | $3.75 | — | 95.3% | — | — | Proprietary |
| Gemini 3.5 FlashGoogle DeepMind | Google DeepMind | 1M | $1.50 | $9.00 | — | — | — | — | Proprietary |
| Gemini 3 FlashGoogle DeepMind | Google DeepMind | — | $0.50 | $3.00 | — | 90.4% | — | 78% | Proprietary |
| Gemini 3 ProGoogle DeepMind | Google DeepMind | 1M | $2.00 | $12.00 | — | 91.9% | 95% | 76.2% | Proprietary |
| Gemini 2.5 Flash-LiteGoogle DeepMind | Google DeepMind | 1M | $0.10 | $0.40 | — | 64.6% | 49.8% | — | Proprietary |
| Gemini 2.5 FlashGoogle DeepMind | Google DeepMind | 1M | $0.30 | $2.50 | — | 78.3% | 78% | — | Proprietary |
| Gemini 2.5 ProGoogle DeepMind | Google DeepMind | 1M | $1.25 | $10.00 | — | 84% | 86.7% | 63.8% | Proprietary |
| Gemma 3 27BGoogle DeepMind | Google DeepMind | 131K | $0.10 | $0.20 | 67.5% | 42.4% | — | — | Gemma Terms of Use |
| Gemma 3 12BGoogle DeepMind | Google DeepMind | 131K | $0.05 | $0.10 | 60.6% | 34.9% | — | — | Gemma Terms of Use |
| Gemma 3 4BGoogle DeepMind | Google DeepMind | 131K | $0.02 | $0.04 | 43.6% | — | — | — | Gemma Terms of Use |
| Gemini 2.0 Flash-LiteGoogle DeepMind | Google DeepMind | 1M | $0.075 | $0.30 | 71.6% | 51.5% | — | — | Proprietary |
| Gemini 2.0 FlashGoogle DeepMind | Google DeepMind | 1M | $0.10 | $0.40 | 77.6% | 62.1% | — | — | Proprietary |
| Gemma 2 27BGoogle DeepMind | Google DeepMind | 8.2K | $0.27 | $0.27 | 56% | — | — | — | Gemma Terms of Use |
| Gemma 2 9BGoogle DeepMind | Google DeepMind | 8.2K | $0.06 | $0.06 | 45% | — | — | — | Gemma Terms of Use |
| Gemini 1.5 ProGoogle DeepMind | Google DeepMind | 2.1M | $1.25 | $5.00 | 75.8% | 59.1% | — | — | Proprietary |
| Gemini 1.5 FlashGoogle DeepMind | Google DeepMind | 1M | $0.075 | $0.30 | 67.3% | 51% | — | — | Proprietary |