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Gemini 3.1 Pro vs MiniMax-01

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 MiniMax-01.

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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MiniMax

MiniMax-01

MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per inference, and can handle a context...

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Technical Specifications

SpecificationGemini 3.1 ProMiniMax-01
ProviderGoogleMiniMax
Context Window2,000,000 tokens1,000,192 tokens
Agent Suitability93/100N/A
Time to First Token (TTFT)420 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2026-04-202025-01-15

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro

$2.00

MiniMax-01

$0.20

Output Price per Million Tokens

Gemini 3.1 Pro

$12.00

MiniMax-01

$1.10

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%vs8100.0%
Gemini 3.1 Pro
MiniMax-01
HumanEvalPython coding & logic synthesis
9460.0%vs7820.0%
Gemini 3.1 Pro
MiniMax-01
MATHComplex mathematical problem solving
8800.0%vs5050.0%
Gemini 3.1 Pro
MiniMax-01
GPQAGraduate-level expert reasoning
8130.0%vs3700.0%
Gemini 3.1 Pro
MiniMax-01
HellaSwagCommonsense reasoning and inference
9840.0%vs8300.0%
Gemini 3.1 Pro
MiniMax-01
MT-BenchMulti-turn conversation flow quality
950.0%vs855.0%
Gemini 3.1 Pro
MiniMax-01

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

MiniMax-01 Quirks & Gotchas

No developer gotchas reported.