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Gemini 2.5 Pro 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 Gemini 2.5 Pro and Gemini 3.1 Pro.

Google

Gemini 2.5 Pro

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...

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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.

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Technical Specifications

SpecificationGemini 2.5 ProGemini 3.1 Pro
ProviderGoogleGoogle
Context Window1,048,576 tokens2,000,000 tokens
Agent Suitability90/10093/100
Time to First Token (TTFT)450 ms420 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-06-172026-04-20

API Pricing Comparison

Input Price per Million Tokens

Gemini 2.5 Pro

$1.25

Gemini 3.1 Pro

$2.00

Output Price per Million Tokens

Gemini 2.5 Pro

$10.00

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
8990.0%vs9280.0%
Gemini 2.5 Pro
Gemini 3.1 Pro
HumanEvalPython coding & logic synthesis
9150.0%vs9460.0%
Gemini 2.5 Pro
Gemini 3.1 Pro
MATHComplex mathematical problem solving
8200.0%vs8800.0%
Gemini 2.5 Pro
Gemini 3.1 Pro
GPQAGraduate-level expert reasoning
7200.0%vs8130.0%
Gemini 2.5 Pro
Gemini 3.1 Pro
HellaSwagCommonsense reasoning and inference
9620.0%vs9840.0%
Gemini 2.5 Pro
Gemini 3.1 Pro
MT-BenchMulti-turn conversation flow quality
930.0%vs950.0%
Gemini 2.5 Pro
Gemini 3.1 Pro

Gemini 2.5 Pro Quirks & Gotchas

  • Legacy model — migrate to Gemini 3.1 Pro for better tool calling and lower latency

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