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MiniMax M1 vs Mistral Small 3.2 24B

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 MiniMax M1 and Mistral Small 3.2 24B.

MiniMax

MiniMax M1

MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...

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Mistral

Mistral Small 3.2 24B

Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...

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Technical Specifications

SpecificationMiniMax M1Mistral Small 3.2 24B
ProviderMiniMaxMistral
Context Window1,000,000 tokens128,000 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitybetastable
API AvailableYesYes
Released Date2025-06-172025-06-20

API Pricing Comparison

Input Price per Million Tokens

MiniMax M1

$0.40

Mistral Small 3.2 24B

$0.07

Output Price per Million Tokens

MiniMax M1

$2.20

Mistral Small 3.2 24B

$0.20

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.

MiniMax M1 Quirks & Gotchas

No developer gotchas reported.

Mistral Small 3.2 24B Quirks & Gotchas

No developer gotchas reported.