Skip to main content

Head-to-head comparison

Claude Opus 4.7 vs. Gemini 3.1 Pro Preview

Compare published benchmark results from matching versions and cohorts, API pricing, and technical specifications. Any documented test setup differences remain visible.

shared result series
37
distinct benchmarks
27
latest retrieval
2026-09-29

Change model selection

Specifications

General specifications

Release date, availability, context window, architecture, and published parameter counts at a glance. Undisclosed details remain marked as unavailable.

Specifications for Claude Opus 4.7 and Gemini 3.1 Pro Preview
AttributeClaude Opus 4.7Gemini 3.1 Pro Preview
ProviderAnthropicGoogle
ReleasedApr 2026Feb 19, 2026
AvailabilityActivePreview
Model typeProprietaryProprietary
ParametersNot publishedNot published
ArchitectureNot publishedNot published
Context window1,000,000 tokens1,048,576 tokens
Knowledge cutoffJanuary 2026Not published
Technical sourcesModel, Knowledge cutoffModel

Pricing

API pricing compared

The table compares official standard API rates per 1M tokens, including published cache pricing. Batch, fast, priority, regional surcharges, tool calls, and cloud platform pricing are excluded.

API pricing for Claude Opus 4.7 and Gemini 3.1 Pro Preview
Price typeClaude Opus 4.7Gemini 3.1 Pro Preview
API input$5$2 ≤200K / $4 >200K
API output$25$12 ≤200K / $18 >200K
Cache read$0.5$0.2 ≤200K / $0.4 >200K
Cache write (5 min.)$6.25Not listed
Cache write (1 hr.)$10Not listed
Price verified09/22/2026 Source09/22/2026 Source
Claude Opus 4.7Gemini 3.1 Pro Preview
API inputUSD per 1M tokens, base tier
Claude Opus 4.7$5
Gemini 3.1 Pro PreviewLower price$2
API outputUSD per 1M tokens, base tier
Claude Opus 4.7$25
Gemini 3.1 Pro PreviewLower price$12
Cache readUSD per 1M tokens, base tier
Claude Opus 4.7$0.5
Gemini 3.1 Pro PreviewLower price$0.2

Key to the marks:better valuebetter, but not conclusivetie

Pricing by provider

Direct developer pricing and provider endpoint tariffs routed through OpenRouter are listed separately. Prices are in USD per 1M tokens. Context-dependent direct tiers plus regional, Flex, Priority, and other OpenRouter tariffs remain individually identifiable.

Provider pricing for Claude Opus 4.7 and Gemini 3.1 Pro Preview
ModelProviderPurchase route and tariffInput per 1M tokensOutput per 1M tokensSource
Claude Opus 4.7AnthropicDirect from developerStandard APILowest listed price: $5Lowest listed price: $25Source09/22/2026
Amazon BedrockVia OpenRouteramazon-bedrock/eu-west-1$5.5$27.5Source10/07/2026
Amazon BedrockVia OpenRouteramazon-bedrock/globalLowest listed price: $5Lowest listed price: $25Source10/07/2026
AnthropicVia OpenRouteranthropicLowest listed price: $5Lowest listed price: $25Source10/07/2026
AzureVia OpenRouterazure/globalLowest listed price: $5Lowest listed price: $25Source10/07/2026
Claude Platform on AWSVia OpenRouterclaude-on-awsLowest listed price: $5Lowest listed price: $25Source10/07/2026
GoogleVia OpenRoutergoogle-vertex/europe$5.5$27.5Source10/07/2026
GoogleVia OpenRoutergoogle-vertex/globalLowest listed price: $5Lowest listed price: $25Source10/07/2026
GoogleVia OpenRoutergoogle-vertex/us$5.5$27.5Source10/07/2026
Gemini 3.1 Pro PreviewGoogleDirect from developerUp to 200,000 context tokens$2$12Source09/22/2026
GoogleDirect from developerAbove 200,000 context tokens$4$18Source09/22/2026
GoogleVia OpenRoutergoogle-vertex/global$2$12Source10/07/2026
GoogleVia OpenRoutergoogle-vertex/global/priority$3.6$21.6Source10/07/2026
Google AI StudioVia OpenRoutergoogle-ai-studio$2$12Source10/07/2026
Google AI StudioVia OpenRoutergoogle-ai-studio/flexLowest listed price: $1Lowest listed price: $6Source10/07/2026
Google AI StudioVia OpenRoutergoogle-ai-studio/priority$3.6$21.6Source10/07/2026

Performance

Shared benchmarks

Only published results with the same benchmark version, task, metric, and comparison cohort are paired. Different reasoning levels, agents, harnesses, or output limits appear directly in the table.

Capability profile from matched benchmarks

Each axis averages directly matched benchmark families. A value of 100 means the stronger value within this pair, not a universal quality score.

255075100CodingReasoningKnowledgeFinanceLegalAgentic tasksMultimodalHealth
Claude Opus 4.7
Gemini 3.1 Pro Preview
Coding: 99.2 / 76.1 (5 benchmark families)
Reasoning: 94.4 / 100 (1 benchmark family)
Knowledge: 88.4 / 100 (2 benchmark families)
Finance: 100 / 86.4 (6 benchmark families)
Legal: 99.2 / 51.2 (3 benchmark families)
Agentic tasks: 98.6 / 97.9 (3 benchmark families)
Multimodal: 97 / 100 (1 benchmark family)
Health: 96.4 / 95.9 (2 benchmark families)

37 matched rows from 26 benchmark families were considered. The radar shows 8 of 10 comparable categories.

Claude Opus 4.7Gemini 3.1 Pro Preview
Code MigrationOverall. Higher is better. No documented setup difference
Claude Opus 4.7Winner43.878 %
Gemini 3.1 Pro Preview17.313 %
CorpFin v2Overall. Higher is better. No documented setup difference
Claude Opus 4.7Winner66.084 %
Gemini 3.1 Pro Preview64.491 %
EMBOverall. Higher is better. No documented setup difference
Claude Opus 4.7Winner63.728 %
Gemini 3.1 Pro Preview52.616 %
Finance Agent (v2)Overall. Higher is better. No documented setup difference
Claude Opus 4.7Winner51.509 %
Gemini 3.1 Pro Preview42.982 %
GAIA ReliabilityAccuracy. Higher is better. No documented setup difference
Claude Opus 4.773.3 %
Gemini 3.1 Pro PreviewWinner76.2 %
GPQA DiamondOverall. Higher is better. No documented setup difference
Claude Opus 4.790.152 %
Gemini 3.1 Pro PreviewWinner95.454 %
Harvey's Legal Agent BenchmarkOverall · Task fully resolved. Higher is better. No documented setup difference
Claude Opus 4.7Winner6.667 %
Gemini 3.1 Pro Preview0 %
Humanity's Last ExamOverall. Higher is better. No documented setup difference
Claude Opus 4.736.20% ± 1.88
Gemini 3.1 Pro PreviewWinner46.44% ± 1.96
Legal Research BenchOverall · All-pass. Higher is better. No documented setup difference
Claude Opus 4.7Winner38.462 %
Gemini 3.1 Pro Preview20.673 %
LegalBenchOverall. Higher is better. No documented setup difference
Claude Opus 4.785.251 %
Gemini 3.1 Pro PreviewWinner87.398 %
LiveCodeBench v6Overall. Higher is better. No documented setup difference
Claude Opus 4.785.073 %
Gemini 3.1 Pro PreviewWinner88.485 %
MedCodeOverall. Higher is better. No documented setup difference
Claude Opus 4.754.858 %
Gemini 3.1 Pro PreviewWinner59.062 %

Key to the marks:better valuebetter, but not conclusivetie

Benchmark scores for Claude Opus 4.7 and Gemini 3.1 Pro Preview
Benchmark and taskClaude Opus 4.7Gemini 3.1 Pro PreviewSource
Code MigrationOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner43.878 %
17.313 %
Vals AI
Source details
Data as of: 09/27/2026
CorpFin v2Overall
Test details
No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better
Winner66.084 %
64.491 %
Vals AI
Source details
Data as of: 08/12/2026
EMBOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner63.728 %
52.616 %
Vals AI
Source details
Data as of: 09/27/2026
Finance Agent (v2)Overall
Test details
No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better
Winner51.509 %
42.982 %
Vals AI
Source details
Data as of: 09/27/2026
GAIA ReliabilityAccuracy
Test details
No documented difference in the test setupVersion: final leak-cleaned public validation setMetric: exact-match accuracyScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability165 GAIA tasks with repeated runs and perturbations. HAL does not publish cost for this evaluation.
73.3 %
Winner76.2 %
Princeton HAL
Source details
Data as of: 08/06/2026
GPQA DiamondOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
90.152 %
Winner95.454 %
Vals AI
Source details
Data as of: 09/01/2026
Harvey's Legal Agent BenchmarkOverall · Task fully resolved
Test details
No documented difference in the test setupVersion: 1Metric: task resolution rateScoring: Higher is better
Winner6.667 %
0 %
Vals AI
Source details
Data as of: 09/27/2026
Humanity's Last ExamOverall
Test details
No documented difference in the test setupVersion: final 2,500-question public setMetric: accuracyScoring: Higher is betterClaude Opus 4.7: Attempts: pass@1
Gemini 3.1 Pro Preview: Snapshot: gemini-3.1-pro-preview-thinking-high, Attempts: pass@1All 2,500 public questions, temperature 0, and an automatic answer extractor.
36.20% ± 1.88
95% confidence interval: ±1.88
Winner46.44% ± 1.96
95% confidence interval: ±1.96		Scale AI
Source details
Data as of: 09/02/2026
Legal Research BenchOverall · All-pass
Test details
No documented difference in the test setupVersion: 1Metric: all-pass rateScoring: Higher is better
Winner38.462 %
20.673 %
Vals AI
Source details
Data as of: 09/27/2026
LegalBenchOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
85.251 %
Winner87.398 %
Vals AI
Source details
Data as of: 09/27/2026
LiveCodeBench v6Overall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
85.073 %
Winner88.485 %
Vals AI
Source details
Data as of: 09/01/2026
MedCodeOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
54.858 %
Winner59.062 %
Vals AI
Source details
Data as of: 09/26/2026
MedScribeOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner82.953 %
76.114 %
Vals AI
Source details
Data as of: 09/26/2026
MMLU-ProOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
89.871 %
Winner90.987 %
Vals AI
Source details
Data as of: 09/01/2026
MMMU-ProOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
85.549 %
Winner88.208 %
Vals AI
Source details
Data as of: 09/01/2026
MortgageTaxOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner70.27 %
69.396 %
Vals AI
Source details
Data as of: 09/01/2026
ProgramBenchOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Tie0 %
Tie0 %
Vals AI
Source details
Data as of: 09/27/2026
SAGEOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner56.103 %
48.677 %
Vals AI
Source details
Data as of: 09/26/2026
SWE-bench VerifiedOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner82 %
78.8 %
Vals AI
Source details
Data as of: 09/01/2026
Tax Agent BenchOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner63.864 %
37.842 %
Vals AI
Source details
Data as of: 09/27/2026
TaxEval v2Overall
Test details
No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better
Winner75.266 %
72.882 %
Vals AI
Source details
Data as of: 09/01/2026
Terminal-Bench 2.0Overall
Test details
No documented difference in the test setupVersion: 2.0Metric: accuracyScoring: Higher is better
Winner68.539 %
67.416 %
Vals AI
Source details
Data as of: 06/04/2026
Terminal-Bench 2.1Overall
Test details
No documented difference in the test setupVersion: 2.1Metric: accuracyScoring: Higher is better
68.539 %
Winner70.787 %
Vals AI
Source details
Data as of: 09/27/2026
Vals IndexOverall
Test details
No documented difference in the test setupVersion: 2Metric: weighted index scoreScoring: Higher is better
Winner56.114 %
41.903 %
Vals AI
Source details
Data as of: 09/27/2026
Vals Multimodal IndexOverall
Test details
No documented difference in the test setupVersion: 1.2Metric: weighted index scoreScoring: Higher is better
Winner67.361 %
56.068 %
Vals AI
Source details
Data as of: 08/11/2026
Vibe Code Bench v1.1Overall
Test details
No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is betterSettings: Harness: OpenHands
Winner71.003 %
32.034 %
Vals AI
Source details
Data as of: 09/27/2026
τ-bench Airline CleanAccuracy
Test details
No documented difference in the test setupVersion: 26-task cleaned subsetMetric: task success rateScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability26 cleaned airline tasks. Princeton HAL recomputed every metric from scratch on this subset.
Winner84.6 %
82.1 %
Princeton HAL
Source details
Data as of: 08/05/2026
GAIA ReliabilityConsistency
Test details
No documented difference in the test setupVersion: final leak-cleaned public validation setMetric: aggregate consistencyScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability165 GAIA tasks with repeated runs and perturbations. HAL does not publish cost for this evaluation.
Winner0.81 rating points
0.76 rating points
Princeton HAL
Source details
Data as of: 08/06/2026
τ-bench Airline CleanConsistency
Test details
No documented difference in the test setupVersion: 26-task cleaned subsetMetric: aggregate consistencyScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability26 cleaned airline tasks. Princeton HAL recomputed every metric from scratch on this subset.
Winner0.88 rating points
0.81 rating points
Princeton HAL
Source details
Data as of: 08/05/2026
GAIA ReliabilityPredictability
Test details
No documented difference in the test setupVersion: final leak-cleaned public validation setMetric: aggregate predictabilityScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability165 GAIA tasks with repeated runs and perturbations. HAL does not publish cost for this evaluation.
0.73 rating points
Winner0.78 rating points
Princeton HAL
Source details
Data as of: 08/06/2026
τ-bench Airline CleanPredictability
Test details
No documented difference in the test setupVersion: 26-task cleaned subsetMetric: aggregate predictabilityScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability26 cleaned airline tasks. Princeton HAL recomputed every metric from scratch on this subset.
Winner0.87 rating points
0.83 rating points
Princeton HAL
Source details
Data as of: 08/05/2026
GAIA ReliabilityReliability
Test details
No documented difference in the test setupVersion: final leak-cleaned public validation setMetric: aggregate reliabilityScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability165 GAIA tasks with repeated runs and perturbations. HAL does not publish cost for this evaluation.
Winner0.84 rating points
0.82 rating points
Princeton HAL
Source details
Data as of: 08/06/2026
τ-bench Airline CleanReliability
Test details
No documented difference in the test setupVersion: 26-task cleaned subsetMetric: aggregate reliabilityScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability26 cleaned airline tasks. Princeton HAL recomputed every metric from scratch on this subset.
Winner0.89 rating points
0.86 rating points
Princeton HAL
Source details
Data as of: 08/05/2026
GAIA ReliabilityRobustness
Test details
No documented difference in the test setupVersion: final leak-cleaned public validation setMetric: aggregate robustnessScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability165 GAIA tasks with repeated runs and perturbations. HAL does not publish cost for this evaluation.
Winner0.99 rating points
0.94 rating points
Princeton HAL
Source details
Data as of: 08/06/2026
τ-bench Airline CleanRobustness
Test details
No documented difference in the test setupVersion: 26-task cleaned subsetMetric: aggregate robustnessScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability26 cleaned airline tasks. Princeton HAL recomputed every metric from scratch on this subset.
0.91 rating points
Winner0.94 rating points
Princeton HAL
Source details
Data as of: 08/05/2026
GAIA ReliabilitySafety
Test details
No documented difference in the test setupVersion: final leak-cleaned public validation setMetric: aggregate safetyScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability165 GAIA tasks with repeated runs and perturbations. HAL does not publish cost for this evaluation.
Tie1 rating points
Tie1 rating points
Princeton HAL
Source details
Data as of: 08/06/2026
τ-bench Airline CleanSafety
Test details
No documented difference in the test setupVersion: 26-task cleaned subsetMetric: aggregate safetyScoring: Higher is betterSettings: Agent: HAL Reliability, Harness: HAL Reliability26 cleaned airline tasks. Princeton HAL recomputed every metric from scratch on this subset.
0.94 rating points
Winner0.97 rating points
Princeton HAL
Source details
Data as of: 08/05/2026

Key to the marks:better valuebetter, but not conclusivetie

Our model tests

Our tests

Compare how the models respond to the same prompt. Each test shows the latest attempt, with no subsequent fixes to the generated code. Earlier runs remain available in the test details. These results do not contribute to an overall score.

Pelican on a bicycle

A community classic for free-form SVG drawing.

Claude Opus 4.7

Claude Opus 4.7: Pelican on a bicycle
A community classic for free-form SVG drawing.

Reasoning (requested): high

Current attempt
Run date
1 Oct 2026
API provider
openrouter
Requested API model
anthropic/claude-opus-4.7
API model reported in response
anthropic/claude-opus-4.7
Reasoning setting
high
Pinned endpoint
Anthropic | anthropic/claude-4.7-opus-20260416
Temperature
Provider default
Token limit including reasoning
8,192 tokens
Test protocol
community-visual-tests-v1
Technical checks
Passed, not a quality rating
Response time
19.9 s

Visually reviewed. This individual test does not establish overall model quality.

Gemini 3.1 Pro Preview

The response reached the token limit. No complete recording is available.

Reasoning (requested): high

Current attempt
Run date
2 Oct 2026
API provider
openrouter
Requested API model
google/gemini-3.1-pro-preview
API model reported in response
google/gemini-3.1-pro-preview
Reasoning setting
high
Pinned endpoint
Google AI Studio | google/gemini-3.1-pro-preview-20260219
Temperature
Provider default
Token limit including reasoning
8,192 tokens
Test protocol
community-visual-tests-v1
Technical checks
Failed
Response time
61.6 s

Not yet visually reviewed. A successful recording does not confirm correct physics or full compliance with the prompt.

Earlier attempts (2)
  • 1 Oct 2026API request failedReasoning setting: high
  • 7 Sept 2026API request failedReasoning setting: high
Prompt and test conditions

Generate an SVG of a pelican riding a bicycle

Token limit including reasoning: 8,192 tokens

Task origin (Simon Willison)

How to read this comparison

Winning one benchmark is not an overall verdict

Your workload, budget, and required context length matter most. A coding benchmark says little about visual understanding or agent performance.

The standard price table uses direct developer rates. The provider comparison labels OpenRouter endpoints, regions, and special tariffs separately.

Every result links to its measurement source and retrieval date. Labels distinguish vendor reports, official benchmark leaderboards, and independent evaluations. Disputed or archived results are excluded.

More matchups

Related LLM comparisons

Compare Claude Opus 4.7 and Gemini 3.1 Pro Preview with other leading models using the same data and benchmark logic.

View the complete LLM comparison