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Data

Data as of October 17, 2026 · How the score is built

EstablishedProprietaryReasoning

Released Feb 19, 20261M context

Gemini 3.1 Pro

Decision readingGemini 3.1 Pro scores 64.7 out of 100 and ranks #37 of 224. This profile shows 30 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #17. API pricing is $2 input and $12 output per million tokens, with cached input at $0.2.

Released Feb 19, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

64.7/100

field median 49.6#37 of 224 ranked models

Public

#37of 224

Verified —

Price

$2input / $12 output

input median $0.75cached $0.20 · batch + cache $0.20 · blended $7

Speed

140tok/s

field median 92 tok/sFirst token 18.99 s

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Multimodal & Grounded ranks #17. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Validate before choosing

30 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #70.

Source-linked · 30 displayable benchmark rows

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #70 of 128Percentile 46thWeight 22%7 benchmarksMixed sources
38.4
CodingRank #67 of 150Percentile 56thWeight 20%6 benchmarksMixed sources
39.2
ReasoningRank Not rankedWeight 17%2 benchmarksVerified
58.2
MultimodalRank #17 of 54Percentile 70thWeight 12%7 benchmarksReported
80.1
KnowledgeRank #26 of 184Percentile 86thWeight 12%6 benchmarksMixed sources
67.6
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathRank Not rankedWeight 5%2 benchmarksVerified
65.0

30 of 681 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic5/7 verified
  2. Coding5/6 verified
  3. Reasoning2/2 verified
  4. Multimodal0/7 verified
  5. Knowledge2/6 verified
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. Math2/2 verified
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Gemini 3.1 Pro category percentile values

  • Agentic46th percentile
  • Coding56th percentile
  • ReasoningNot eligible
  • Multimodal70th percentile
  • Knowledge86th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#70/128
  2. Coding#67/150
  3. ReasoningNot ranked
  4. Multimodal#17/54
  5. Knowledge#26/184
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding6 rows
Coding benchmark values, best verified comparison, weight, and source status
LiveCodeBench (Vals)LiveCodeBench, Vals AI runScore88.5%Versus best verified row

Best verified: Claude Fable 5.1 · 90.5%

Gap2 behindWeight8% ref. weight
LiveCodeBench ProScore82.9%Versus best verified row

Best verified: Sakana Fugu-Ultra · 90.8%

Gap7.9 behindWeightDisplay only
React Native EvalsScore78.9%Versus best verified row

Best verified: Composer 2 · 96.1%

Gap17.2 behindWeightDisplay only
Vibe Code BenchVibe Code Bench v1.1Score32.03%Versus best verified row

Best verified: Gemini 4 Argon · 91.90%

Gap59.9 behindWeightDisplay only
SWE-bench (Vals)SWE-bench, Vals AI runScore78.8%Versus best verified row

Best verified: Claude Opus 5 · 97.0%

Gap18.2 behindWeightDisplay only
PostTrainBench v1.1Score22.0%Versus best verified row

Best verified: Claude Opus 5.5 · 49.3%

Gap27.3 behindWeightDisplay only
Agentic7 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore70.8%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap16.5 behindWeight4% ref. weight
DeepSearchQAScore69.7%Versus best verified row

Best verified: Atria Dawn Preview · 96.0%

Gap26.3 behindWeight2% ref. weight
Claw-EvalScore57.8%Versus best verified row

Best verified: Ornith-1.5-397B · 81.4%

Gap23.6 behindWeightDisplay only
Benchmark exact
τ²-bench resultsτ²-Bench Tool-Agent-User EvaluationScore95.6%Versus best verified row

Best verified: GPT-5.4 · 98.9%

Gap3.3 behindWeightDisplay only
Gert LabsGert Labs Composite Game BenchmarkScore56.87%Versus best verified row

Best verified: Claude Opus 4.8 · 72.97%

Gap16.1 behindWeightDisplay only
Benchmark exact
ResearchClawBenchScore13.3%Versus best verified row

Best verified: Claude Opus 4.8 · 21.1%

Gap7.8 behindWeightDisplay only
MazeBenchMazeBench: visual spatial reasoning in a 3D open worldScore1%Versus best verified row

Best verified: GPT-6 Astra · 23%

Gap22 behindWeightDisplay only
Reasoning2 rows
Reasoning benchmark values, best verified comparison, weight, and source status
ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2Score77.1%Versus best verified row

Best verified: GPT-6 Astra · 95%

Gap17.9 behindWeightWeighted 25%
ARC-AGI-3Abstraction and Reasoning Corpus for AGI v3Score0.4%Versus best verified row

Best verified: GPT-6 Astra · 62.7%

Gap62.3 behindWeightWeighted 15%
Multimodal7 rows
Multimodal benchmark values, best verified comparison, weight, and source status
MMMU-ProMassive Multi-discipline Multimodal Understanding ProScore83.9%Versus best verified row

Best verified: Gemini 3.5 Flash · 83.6%

Gap0.3 behindWeightWeighted 40%
CharXivCharXiv ReasoningScore80.2%Versus best verified row

Best verified: Qwen3.8 Max · 93.5%

Gap13.3 behindWeightWeighted 20%
ERQAScore69.4%Versus best verified row

Best verified: Qwen3.8 Max · 77.8%

Gap8.4 behindWeightDisplay only
SimpleVQAScore72.4%Versus best verified row

Best verified: Qwen3.7 Plus · 81.7%

Gap9.3 behindWeightDisplay only
ScreenSpot ProScore84.4%Versus best verified row

Best verified: GPT-6 Astra · 92.7%

Gap8.3 behindWeightDisplay only
ZeroBenchScore29.0%Versus best verified row

Best verified: Muse Spark Open · 50.0%

Gap21 behindWeightDisplay only
MedXpertQA (MM)MedXpertQA MultimodalScore81.3%Versus best verified row

Best verified: Qwen3.8 Max · 80.4%

Gap0.9 behindWeightDisplay only
Knowledge6 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLE w/o toolsHumanity's Last Exam without toolsScore45.4%Versus best verified row

Best verified: Claude Opus 5.5 · 64.4%

Gap19 behindWeight7% ref. weight
MMLU-Pro (Vals)MMLU-Pro, Vals AI runScore91.0%Versus best verified row

Best verified: Claude Fable 5.1 · 92.4%

Gap1.4 behindWeight6% ref. weight
GPQA Diamond (Vals)GPQA Diamond, Vals AI runScore95.5%Versus best verified row

Best verified: Gemini 3.1 Pro · 95.5%

GapBest verifiedWeight2% ref. weight
GPQA-DGPQA DiamondScore94.3%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap1.7 behindWeightDisplay only
HealthBench HardScore20.6%Versus best verified row

Best verified: Muse Spark · 42.8%

Gap22.2 behindWeightDisplay only
MedXpertQA (Text)MedXpertQA TextScore71.5%Versus best verified row

Best verified: Muse Spark · 52.6%

Gap18.9 behindWeightDisplay only
Math2 rows
Math benchmark values, best verified comparison, weight, and source status
FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3Score59.649%Versus best verified row

Best verified: GPT-6 Astra · 93.684%

Gap34 behindWeightWeighted 30%
FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4Score26.829%Versus best verified row

Best verified: GPT-6.1 Sol · 100.000%

Gap73.2 behindWeightWeighted 10%

Bars run 0–100; the dark tick marks the best source-verified value

All 30 rows

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Current modelExplore all models

Gemini 3.1 Pro · 64.7 score · $7 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierGemini 3.1 Pro

Horizontal: blended price per million tokens, log scale · Vertical: public score

Published price history

This chart appears only when at least two dated first-party price records exist for the exact model. It shows rate changes, not an inferred cost trend.

08152026-042026-072026-10Output priceInput price

3 dated first-party price records. The newest record lists $12 per million tokens.

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Feb 19, 2026 · you are here

    Gemini 3.1 Pro

    Score 64.7 · $2 / $12

Base entry

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
gemini-3.1-pro-previewGoogle Gemini 3.1 Pro Preview model documentation
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
text, image, video, audio, pdfGoogle Gemini 3.1 Pro Preview model documentation
Parameters
Not disclosed by the provider
Availability
Gemini API · Google AI StudioGoogle Gemini 3.1 Pro Preview model documentation
Cloud regions
Not tracked yet
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.20 per million cached input tokensGoogle Gemini API pricing
Self-host
Weights are not published
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Gemini 3.1 Pro ranks #37 of 224 on the public leaderboard with a score of 64.7/100. It does not yet have enough sourced coverage for a verified position.

Gemini 3.1 Pro is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

30 of 681 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Multimodal & Grounded at #17, while its lowest eligible position is Agentic at #70. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Last updated October 17, 2026. Runtime fields remain blank until a sourced snapshot exists.

Questions

How does Gemini 3.1 Pro perform overall in AI benchmarks?

Gemini 3.1 Pro ranks #37 out of 224 models on the public BenchAlign leaderboard, with a score of 64.7/100. Its evidence status is Estimated, and this profile shows 30 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Gemini 3.1 Pro good for knowledge and understanding?

Gemini 3.1 Pro ranks #26 out of 184 eligible models for knowledge and understanding, with a public category score of 67.6/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Gemini 3.1 Pro good for coding and programming?

Gemini 3.1 Pro ranks #67 out of 150 eligible models for coding and programming, with a public category score of 39.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Gemini 3.1 Pro good for mathematics?

Gemini 3.1 Pro has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Gemini 3.1 Pro good for reasoning and logic?

Gemini 3.1 Pro has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Gemini 3.1 Pro good for agentic tool use and computer tasks?

Gemini 3.1 Pro ranks #70 out of 128 eligible models for agentic tool use and computer tasks, with a public category score of 38.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Gemini 3.1 Pro good for multimodal and grounded tasks?

Gemini 3.1 Pro ranks #17 out of 54 eligible models for multimodal and grounded tasks, with a public category score of 80.1/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Does Gemini 3.1 Pro have full benchmark coverage on BenchLM?

No. Gemini 3.1 Pro currently has 48 source-displayable rows across 681 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Gemini 3.1 Pro?

Gemini 3.1 Pro has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

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Compare Gemini 3.1 Pro with every tracked model953 comparisons