Model comparison

Claude Opus 4.6 (Adaptive) vs Gemini 3.1 Pro

Updated July 29, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Claude Opus 4.6 (Adaptive)

Anthropic

63.4/100

Estimated · Public rank #38

90% interval 51.9–75.0

Gemini 3.1 Pro

Google

54.7/100

Estimated · Public rank #87

90% interval 38.8–70.6

Claude Opus 4.6 (Adaptive) has the higher public score estimate, 63.44 versus 54.66, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

What is actually comparable

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

1 Shared

22 Gemini 3.1 Pro only

Shared results: 1
Claude Opus 4.6 (Adaptive) only: 0
Gemini 3.1 Pro only: 22
Like-for-like categories: 0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Coding

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Reasoning

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: 77.1
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Knowledge

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Math

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: 31.8
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Multilingual

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Multimodal

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: 82.6
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Instruction following

Not comparable

Claude Opus 4.6 (Adaptive): Not measured
Gemini 3.1 Pro: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Claude Opus 4.6 (Adaptive) and Gemini 3.1 Pro
Category	Claude Opus 4.6 (Adaptive)	Gemini 3.1 Pro	Weighted basis	Reading
Agentic	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Coding	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Reasoning	Not measured	77.1	Not comparable0 vs 1 rows	Not comparable
Knowledge	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Math	Not measured	31.8	Not comparable0 vs 2 rows	Not comparable
Multilingual	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Multimodal	Not measured	82.6	Not comparable0 vs 2 rows	Not comparable
Instruction following	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable

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

Claude Opus 4.6 (Adaptive): API rate not published; Fits in one request
Gemini 3.1 Pro: $0.008; Fits in one request

Claude Opus 4.6 (Adaptive) has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.6 (Adaptive): API rate not published; Fits in one request
Gemini 3.1 Pro: $0.136; Fits in one request

Claude Opus 4.6 (Adaptive) has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Opus 4.6 (Adaptive): API rate not published; Fits in one request; Cached-input rate unavailable
Gemini 3.1 Pro: $0.2; Fits in one request

Claude Opus 4.6 (Adaptive) has no comparable published API token rate.

Specification differences

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

SpecificationClaude Opus 4.6 (Adaptive)Gemini 3.1 Pro

Claude Opus 4.6 (Adaptive)

Reasoning

Gemini 3.1 Pro

Reasoning

Weight access

Claude Opus 4.6 (Adaptive)

Proprietary

Gemini 3.1 Pro

Proprietary

License

Claude Opus 4.6 (Adaptive)

Proprietary

Gemini 3.1 Pro

Proprietary

Release date

Claude Opus 4.6 (Adaptive)

2026-02-01

Gemini 3.1 Pro

2026-02-19

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: Claude Opus 4.6 (Adaptive) has the higher public score estimate, 63.44 versus 54.66, but the 90% score intervals overlap.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Both models list 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 evidence23 rows

Agentic

Claw-Eval
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro57.8%
Source
Not directly comparable
DeepSearchQA
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro69.7%
Source
Not directly comparable
τ²-bench results
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro95.6%
Source
Not directly comparable
Gert Labs
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro56.87%
Source
Not directly comparable
ResearchClawBench
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro13.3%
Source
Not directly comparable

Coding

Vibe Code Bench
Shared source
Claude Opus 4.6 (Adaptive)53.50%
Gemini 3.1 Pro32.03%
Claude Opus 4.6 (Adaptive) leads this result
LiveCodeBench Pro
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro82.9%
Source
Not directly comparable
React Native Evals
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro78.9%
Source
Not directly comparable

Reasoning

ARC-AGI-2
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro77.1%
Source
Not directly comparable
ARC-AGI-3
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro0.4%
Source
Not directly comparable

Knowledge

GPQA-D
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro94.3%
Source
Not directly comparable
HLE w/o tools
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro45.4%
Source
Not directly comparable
HealthBench Hard
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro20.6%
Source
Not directly comparable
MedXpertQA (Text)
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro71.5%
Source
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro36.900%
Source
Not directly comparable
FrontierMath v2 (Tier 4)
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro16.700%
Source
Not directly comparable

Multimodal

MMMU-Pro
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro83.9%
Source
Not directly comparable
CharXiv
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro80.2%
Source
Not directly comparable
ERQA
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro69.4%
Source
Not directly comparable
SimpleVQA
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro72.4%
Source
Not directly comparable
ScreenSpot Pro
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro84.4%
Source
Not directly comparable
ZeroBench
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro29.0%
Source
Not directly comparable
MedXpertQA (MM)
Claude Opus 4.6 (Adaptive)—
Gemini 3.1 Pro81.3%
Source
Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Claude Opus 4.6 (Adaptive) has the higher public score estimate, 63.44 versus 54.66, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated July 29, 2026

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Claude Opus 4.6 (Adaptive) vs Gemini 3.1 Pro

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multimodal

Frequently asked questions

Which is better, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Which is better for coding, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Which is better for agentic tasks, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Which costs less, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Which has the larger context window, Claude Opus 4.6 (Adaptive) or Gemini 3.1 Pro?

Related comparisons

Watch Claude Opus 4.6 (Adaptive) vs Gemini 3.1 Pro