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Gemini 3.1 Pro vs Mixtral 8x22B Instruct

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 Mixtral 8x22B Instruct.

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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Mistral

Mixtral 8x22B Instruct

Mistral's official instruct fine-tuned version of [Mixtral 8x22B](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,...

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Technical Specifications

SpecificationGemini 3.1 ProMixtral 8x22B Instruct
ProviderGoogleMistral
Context Window2,000,000 tokens65,536 tokens
Agent Suitability93/100N/A
Time to First Token (TTFT)420 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202024-04-17

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro

$2.00

Mixtral 8x22B Instruct

$2.00

Output Price per Million Tokens

Gemini 3.1 Pro

$12.00

Mixtral 8x22B Instruct

$6.00

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%vsN/A
Gemini 3.1 Pro
Mixtral 8x22B Instruct
HumanEvalPython coding & logic synthesis
9460.0%vsN/A
Gemini 3.1 Pro
Mixtral 8x22B Instruct
MATHComplex mathematical problem solving
8800.0%vsN/A
Gemini 3.1 Pro
Mixtral 8x22B Instruct
GPQAGraduate-level expert reasoning
8130.0%vsN/A
Gemini 3.1 Pro
Mixtral 8x22B Instruct
HellaSwagCommonsense reasoning and inference
9840.0%vsN/A
Gemini 3.1 Pro
Mixtral 8x22B Instruct
MT-BenchMulti-turn conversation flow quality
950.0%vsN/A
Gemini 3.1 Pro
Mixtral 8x22B Instruct

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

Mixtral 8x22B Instruct Quirks & Gotchas

No developer gotchas reported.