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BenchLM
Data

Gemini 3.1 Pro vs Gemini 3 Pro

Updated October 17, 2026. Rank says Gemini 3.1 Pro is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Gemini 3.1 Pro has the higher public point estimate, 64.7 versus 61.18. Their conditional score ranges overlap. These ranges do not establish rank confidence. 8 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Google logo

Google

64.7/100

Estimated · Public rank #37

Conditional range 55.0–74.4

Model B
Google logo

Google

61.18/100

Supported · Public rank #52

90% interval 50.3–72.0

Shared results
8
Gemini 3.1 Pro only
22
Gemini 3 Pro only
19
Like-for-like categories
1 / 8
Estimated: Gemini 3.1 Pro · Supported: Gemini 3 Pro. Conditional ranges do not establish rank confidence.How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Gemini 3 Pro

    Gemini 3 Pro has the larger documented context window.

    Confidence: documented
  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Gemini 3.1 Pro

    Gemini 3.1 Pro has the lower estimated token cost for this stated workload. Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback
Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Gemini 3 Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    Gemini 3 Pro is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited
  • Chat turn cost

    1K fresh input + 500 output tokens

    No clear pick

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates
  • Repository review cost

    50K fresh input + 3K output tokens

    No clear pick

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

39.2Gemini 3.1 Pro43.0Gemini 3 Pro

Directional only · BenchAlign v5.8

Gemini 3 Pro has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Multimodal

Like-for-like
Gemini 3.1 Pro
80.1
#17/54
Gemini 3 Pro
80.0
#18/54
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Practical tie

Coding

Directional only
Gemini 3.1 Pro
39.2
Supported · #67/150
Gemini 3 Pro
43.0
Estimated · #59/150
Basis
BenchAlign v5.8 lane · 6 vs 1 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 3.1 Pro
67.6
Supported · #26/184
Gemini 3 Pro
60.8
Estimated · #47/184
Basis
BenchAlign v5.8 lane · 6 vs 0 public rows
Reading
Directional only

Agentic

Not comparable
Gemini 3.1 Pro
38.4
Supported · #70/128
Gemini 3 Pro
Not ranked
Basis
BenchAlign v5.8 lane · 7 vs 2 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.1 Pro
58.2
Unranked · 2 rankable rows
Gemini 3 Pro
50.1
Unranked · 4 rankable rows
Basis
Provisional lane · 2 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.1 Pro
Not ranked
Gemini 3 Pro
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.1 Pro
Not ranked
Gemini 3 Pro
86.1
#45/148
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.1 Pro
65.0
Unranked · 2 rankable rows
Gemini 3 Pro
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Gemini 3.1 Pro
$0.008
Fits in one request
Gemini 3 Pro
$0.008
Fits in one request

Modeled costs are equal

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.1 Pro
$0.136
Fits in one request
Gemini 3 Pro
$0.136
Fits in one request

Modeled costs are equal

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Gemini 3.1 Pro
$0.2
Fits in one request
Gemini 3 Pro
$0.56
Fits in one request
Cached input priced at the published list-input rate

Gemini 3.1 Pro has the lower modeled cost

Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Gemini 3.1 Pro

$0.2 per 1M cached input tokens

Google Gemini API pricing

Gemini 3 Pro

Not published

Reasoning profile

Gemini 3.1 Pro

Reasoning

Gemini 3 Pro

Non-Reasoning

Weight access

Gemini 3.1 Pro

Proprietary

Gemini 3 Pro

Proprietary

License

Gemini 3.1 Pro

Proprietary

Gemini 3 Pro

Proprietary

Release date

Gemini 3.1 Pro

2026-02-19

Gemini 3 Pro

2025-11-18

If you already use one of these models

Deployment change
Both entries list Google as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
Gemini 3.1 Pro has the higher public point estimate, 64.7 versus 61.18. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost
Repository review: $0.136 vs $0.136. Cache-heavy agent loop: $0.2 vs $0.56.
Context tradeoff
Gemini 3 Pro has the larger documented window (2M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 3.1 Pro or Gemini 3 Pro?

Gemini 3.1 Pro has the higher public point estimate, 64.7 versus 61.18. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 3.1 Pro or Gemini 3 Pro?

Gemini 3 Pro scores higher for coding on the public lane, 43 to 39.2. Gemini 3 Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Gemini 3.1 Pro or Gemini 3 Pro?

Gemini 3 Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Gemini 3.1 Pro or Gemini 3 Pro?

For the stated presets, chat costs $0.008 on Gemini 3.1 Pro and $0.008 on Gemini 3 Pro; repository review costs $0.136 and $0.136; the cache-heavy agent loop costs $0.2 and $0.56. Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Gemini 3.1 Pro or Gemini 3 Pro?

Gemini 3 Pro has the larger documented context window: 2M, compared with 1M.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence49 rows

Agentic

  • Claw-Eval

    Gemini 3.1 Pro57.8%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • DeepSearchQA

    Gemini 3.1 Pro69.7%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • τ²-bench results

    Gemini 3.1 Pro95.6%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • Gemini 3.1 Pro56.87%
    Gemini 3 Pro63.23%

    Gemini 3 Pro leads this result

  • ResearchClawBench

    Gemini 3.1 Pro13.3%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.1 Pro70.8%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • MazeBench

    Gemini 3.1 Pro1%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • JobBench

    Gemini 3.1 Pro—
    Gemini 3 Pro11.4%
    Source

    Not directly comparable

Coding

  • LiveCodeBench Pro

    Gemini 3.1 Pro82.9%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • React Native Evals

    Gemini 3.1 Pro78.9%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • Vibe Code Bench

    Shared source
    Gemini 3.1 Pro32.03%
    Gemini 3 Pro14.30%

    Gemini 3.1 Pro leads this result

  • LiveCodeBench (Vals)

    Gemini 3.1 Pro88.5%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3.1 Pro78.8%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • PostTrainBench v1.1

    Gemini 3.1 Pro22.0%
    Source
    Gemini 3 Pro—

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Gemini 3.1 Pro77.1%
    Source
    Gemini 3 Pro31.1%
    Source

    Gemini 3.1 Pro leads this result

  • ARC-AGI-3

    Gemini 3.1 Pro0.4%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • ARC-AGI-1

    Gemini 3.1 Pro—
    Gemini 3 Pro75.00%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Gemini 3.1 Pro83.9%
    Source
    Gemini 3 Pro81%
    Source

    Gemini 3.1 Pro leads this result

  • CharXiv

    Gemini 3.1 Pro80.2%
    Source
    Gemini 3 Pro81.4%
    Source

    Gemini 3 Pro leads this result

  • ERQA

    Gemini 3.1 Pro69.4%
    Source
    Gemini 3 Pro70.5%
    Source

    Gemini 3 Pro leads this result

  • SimpleVQA

    Gemini 3.1 Pro72.4%
    Source
    Gemini 3 Pro73.2%
    Source

    Gemini 3 Pro leads this result

  • ScreenSpot Pro

    Gemini 3.1 Pro84.4%
    Source
    Gemini 3 Pro72.7%
    Source

    Gemini 3.1 Pro leads this result

  • ZeroBench

    Gemini 3.1 Pro29.0%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • MedXpertQA (MM)

    Gemini 3.1 Pro81.3%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • MMMU

    Gemini 3.1 Pro—
    Gemini 3 Pro87.2%
    Source

    Not directly comparable

  • RealWorldQA

    Gemini 3.1 Pro—
    Gemini 3 Pro83.3%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Gemini 3.1 Pro—
    Gemini 3 Pro88.5%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Gemini 3.1 Pro—
    Gemini 3 Pro88.4%
    Source

    Not directly comparable

  • Video-MME (w/o subtitle)

    Gemini 3.1 Pro—
    Gemini 3 Pro87.7%
    Source

    Not directly comparable

  • MathVision

    Gemini 3.1 Pro—
    Gemini 3 Pro86.6%
    Source

    Not directly comparable

  • We-Math

    Gemini 3.1 Pro—
    Gemini 3 Pro86.9%
    Source

    Not directly comparable

  • DynaMath

    Gemini 3.1 Pro—
    Gemini 3 Pro85.1%
    Source

    Not directly comparable

  • MMLongBench-Doc

    Gemini 3.1 Pro—
    Gemini 3 Pro60.5%
    Source

    Not directly comparable

  • CC-OCR

    Gemini 3.1 Pro—
    Gemini 3 Pro79.0%
    Source

    Not directly comparable

  • AI2D_TEST

    Gemini 3.1 Pro—
    Gemini 3 Pro94.1%
    Source

    Not directly comparable

  • CountBench

    Gemini 3.1 Pro—
    Gemini 3 Pro97.3%
    Source

    Not directly comparable

  • RefCOCO (avg)

    Gemini 3.1 Pro—
    Gemini 3 Pro84.1%
    Source

    Not directly comparable

  • ODINW13

    Gemini 3.1 Pro—
    Gemini 3 Pro46.3%
    Source

    Not directly comparable

  • VideoMMMU

    Gemini 3.1 Pro—
    Gemini 3 Pro87.6%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Gemini 3.1 Pro—
    Gemini 3 Pro83.0%
    Source

    Not directly comparable

  • V*

    Gemini 3.1 Pro—
    Gemini 3 Pro88.0%
    Source

    Not directly comparable

Knowledge

  • GPQA-D

    Gemini 3.1 Pro94.3%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • HLE w/o tools

    Gemini 3.1 Pro45.4%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • HealthBench Hard

    Gemini 3.1 Pro20.6%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • MedXpertQA (Text)

    Gemini 3.1 Pro71.5%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • GPQA Diamond (Vals)

    Gemini 3.1 Pro95.5%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • MMLU-Pro (Vals)

    Gemini 3.1 Pro91.0%
    Source
    Gemini 3 Pro—

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3.1 Pro59.649%
    Source
    Gemini 3 Pro—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3.1 Pro26.829%
    Source
    Gemini 3 Pro—

    Not directly comparable

49 public results · 8 shared

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Last updated October 17, 2026