← Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Claude Opus 4.6 vs Gemini 3.1 Pro

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Opus 4.6 and Gemini 3.1 Pro.

Anthropic

Claude Opus 4.6

Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective...

View Full Specs
Google

Gemini 3.1 Pro

Google's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.

View Full Specs

Technical Specifications

SpecificationClaude Opus 4.6Gemini 3.1 Pro
ProviderAnthropicGoogle
Context Window1,000,000 tokens2,000,000 tokens
Agent Suitability95/10093/100
Time to First Token (TTFT)500 ms420 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-02-042026-04-20

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.6

$5.00

Gemini 3.1 Pro

$2.00

Output Price per Million Tokens

Claude Opus 4.6

$25.00

Gemini 3.1 Pro

$12.00

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9250.0%vs9280.0%
Claude Opus 4.6
Gemini 3.1 Pro
HumanEvalPython coding & logic synthesis
9450.0%vs9460.0%
Claude Opus 4.6
Gemini 3.1 Pro
MATHComplex mathematical problem solving
8890.0%vs8800.0%
Claude Opus 4.6
Gemini 3.1 Pro
GPQAGraduate-level expert reasoning
7980.0%vs8130.0%
Claude Opus 4.6
Gemini 3.1 Pro
HellaSwagCommonsense reasoning and inference
9750.0%vs9840.0%
Claude Opus 4.6
Gemini 3.1 Pro
MT-BenchMulti-turn conversation flow quality
965.0%vs950.0%
Claude Opus 4.6
Gemini 3.1 Pro

Claude Opus 4.6 Quirks & Gotchas

  • Best for long-context document analysis and legal review
  • Tool calling requires structured prompt — prone to verbose refusal without explicit output schema

Gemini 3.1 Pro Quirks & Gotchas

  • Best model for massive context — 2M token window is class-leading
  • Tool calling requires explicit schema definition in Google AI Studio