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BenchLM

Gemini 3.1 Pro vs Grok 4.7

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Google logo
Model A
Gemini 3.1 Pro

Google

70.46/100

Supported · Public rank #15

90% interval 63.7–77.2

xAI logo
Model B
Grok 4.7

xAI

—

Evidence status unavailable

90% interval unavailable

Updated September 21, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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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 3.1 Pro

    Gemini 3.1 Pro has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Grok 4.7

    Grok 4.7 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    Grok 4.7

    Grok 4.7 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Grok 4.7 is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Grok 4.7 is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K 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.

47.0Gemini 3.1 Pro—Grok 4.7

Not comparable · BenchAlign

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

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

Open the coding leaderboardShortlist models for this job

What is actually comparable

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

Shared results
1
Gemini 3.1 Pro only
27
Grok 4.7 only
5
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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.

Agentic

Not comparable
Gemini 3.1 Pro
40.4
Supported · #118/154
Grok 4.7
Not ranked
Basis
BenchAlign lane · 6 vs 2 public rows
Reading
Not comparable

Coding

Not comparable
Gemini 3.1 Pro
47.0
Supported · #83/156
Grok 4.7
Not ranked
Basis
BenchAlign lane · 5 vs 3 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.1 Pro
50.7
Unranked · 2 rankable rows
Grok 4.7
73.7
Unranked · 2 rankable rows
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.1 Pro
79.1
#12/49
Grok 4.7
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Gemini 3.1 Pro
66.4
Supported · #21/186
Grok 4.7
Not ranked
Basis
BenchAlign lane · 6 vs 1 public rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.1 Pro
Not ranked
Grok 4.7
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.1 Pro
Not ranked
Grok 4.7
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.1 Pro
54.2
Unranked · 2 rankable rows
Grok 4.7
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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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
Grok 4.7
$0.005
Fits in one request

Grok 4.7 has the lower modeled cost

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
Grok 4.7
$0.118
Fits in one request

Grok 4.7 has the lower modeled cost

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
Grok 4.7
$0.2
Fits in one request

Modeled costs are equal

Costs use the listed standard API rates.

Specification differences

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

Reasoning profile

Gemini 3.1 Pro

Reasoning

Grok 4.7

Reasoning

Weight access

Gemini 3.1 Pro

Proprietary

Grok 4.7

Proprietary

License

Gemini 3.1 Pro

Proprietary

Grok 4.7

Proprietary

Release date

Gemini 3.1 Pro

2026-02-19

Grok 4.7

2026-09-21

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
Repository review: $0.136 vs $0.118. Cache-heavy agent loop: $0.2 vs $0.2.
Context tradeoff
Gemini 3.1 Pro has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

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

Browse raw public benchmark evidence33 rows

Agentic

  • Claw-Eval

    Gemini 3.1 Pro57.8%
    Source
    Grok 4.7—

    Not directly comparable

  • DeepSearchQA

    Gemini 3.1 Pro69.7%
    Source
    Grok 4.7—

    Not directly comparable

  • τ²-bench results

    Gemini 3.1 Pro95.6%
    Source
    Grok 4.7—

    Not directly comparable

  • Gert Labs

    Gemini 3.1 Pro56.87%
    Source
    Grok 4.7—

    Not directly comparable

  • ResearchClawBench

    Gemini 3.1 Pro13.3%
    Source
    Grok 4.7—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.1 Pro70.8%
    Source
    Grok 4.776.0%
    Source

    Grok 4.7 leads this result

  • Terminal-Bench 4.0

    Gemini 3.1 Pro—
    Grok 4.738.00%
    Source

    Not directly comparable

Coding

  • LiveCodeBench Pro

    Gemini 3.1 Pro82.9%
    Source
    Grok 4.7—

    Not directly comparable

  • React Native Evals

    Gemini 3.1 Pro78.9%
    Source
    Grok 4.7—

    Not directly comparable

  • Vibe Code Bench

    Gemini 3.1 Pro32.03%
    Source
    Grok 4.7—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.1 Pro88.5%
    Source
    Grok 4.7—

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3.1 Pro78.8%
    Source
    Grok 4.7—

    Not directly comparable

  • cursorBench40

    Gemini 3.1 Pro—
    Grok 4.746.3%
    Source

    Not directly comparable

  • DeepSWE

    Gemini 3.1 Pro—
    Grok 4.771.0%
    Source

    Not directly comparable

  • EEBench

    Gemini 3.1 Pro—
    Grok 4.764.0%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Gemini 3.1 Pro77.1%
    Source
    Grok 4.7—

    Not directly comparable

  • ARC-AGI-3

    Gemini 3.1 Pro0.4%
    Source
    Grok 4.7—

    Not directly comparable

Multimodal

  • MMMU-Pro

    Gemini 3.1 Pro83.9%
    Source
    Grok 4.7—

    Not directly comparable

  • CharXiv

    Gemini 3.1 Pro80.2%
    Source
    Grok 4.7—

    Not directly comparable

  • ERQA

    Gemini 3.1 Pro69.4%
    Source
    Grok 4.7—

    Not directly comparable

  • SimpleVQA

    Gemini 3.1 Pro72.4%
    Source
    Grok 4.7—

    Not directly comparable

  • ScreenSpot Pro

    Gemini 3.1 Pro84.4%
    Source
    Grok 4.7—

    Not directly comparable

  • ZeroBench

    Gemini 3.1 Pro29.0%
    Source
    Grok 4.7—

    Not directly comparable

  • MedXpertQA (MM)

    Gemini 3.1 Pro81.3%
    Source
    Grok 4.7—

    Not directly comparable

Knowledge

  • GPQA-D

    Gemini 3.1 Pro94.3%
    Source
    Grok 4.7—

    Not directly comparable

  • HLE w/o tools

    Gemini 3.1 Pro45.4%
    Source
    Grok 4.7—

    Not directly comparable

  • HealthBench Hard

    Gemini 3.1 Pro20.6%
    Source
    Grok 4.7—

    Not directly comparable

  • MedXpertQA (Text)

    Gemini 3.1 Pro71.5%
    Source
    Grok 4.7—

    Not directly comparable

  • GPQA Diamond (Vals)

    Gemini 3.1 Pro95.5%
    Source
    Grok 4.7—

    Not directly comparable

  • MMLU-Pro (Vals)

    Gemini 3.1 Pro91.0%
    Source
    Grok 4.7—

    Not directly comparable

  • HealthBench Professional

    Gemini 3.1 Pro—
    Grok 4.756.7%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3.1 Pro36.900%
    Source
    Grok 4.7—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3.1 Pro16.700%
    Source
    Grok 4.7—

    Not directly comparable

Questions

Which is better, Gemini 3.1 Pro or Grok 4.7?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 3.1 Pro or Grok 4.7?

Grok 4.7 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Gemini 3.1 Pro or Grok 4.7?

Grok 4.7 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 Grok 4.7?

For the stated presets, chat costs $0.008 on Gemini 3.1 Pro and $0.005 on Grok 4.7; repository review costs $0.136 and $0.118; the cache-heavy agent loop costs $0.2 and $0.2. Costs use the listed standard API rates.

Which has the larger context window, Gemini 3.1 Pro or Grok 4.7?

Gemini 3.1 Pro has the larger documented context window: 1M, compared with 500K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 21, 2026

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