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Gemini 3.1 Pro vs o1

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 3.1 Pro and o1.

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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OpenAI

o1

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...

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Technical Specifications

SpecificationGemini 3.1 Proo1
ProviderGoogleOpenAI
Context Window2,000,000 tokens200,000 tokens
Agent Suitability93/10088/100
Time to First Token (TTFT)420 ms2500 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202024-12-17

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro

$2.00

o1

$15.00

Output Price per Million Tokens

Gemini 3.1 Pro

$12.00

o1

$60.00

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
9280.0%vs9180.0%
Gemini 3.1 Pro
o1
HumanEvalPython coding & logic synthesis
9460.0%vs9450.0%
Gemini 3.1 Pro
o1
MATHComplex mathematical problem solving
8800.0%vs9480.0%
Gemini 3.1 Pro
o1
GPQAGraduate-level expert reasoning
8130.0%vs7830.0%
Gemini 3.1 Pro
o1
HellaSwagCommonsense reasoning and inference
9840.0%vs9200.0%
Gemini 3.1 Pro
o1
MT-BenchMulti-turn conversation flow quality
950.0%vs940.0%
Gemini 3.1 Pro
o1

Gemini 3.1 Pro Quirks & Gotchas

  • โ–ธBest model for massive context โ€” 2M token window is class-leading
  • โ–ธTool calling requires explicit schema definition in Google AI Studio

o1 Quirks & Gotchas

  • โ–ธReasoning model โ€” high latency by design, not for real-time use
  • โ–ธBest for complex math/code reasoning where accuracy > speed
  • โ–ธUse o3-mini when you need reasoning with lower latency