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DeepSeek V3.1 vs Mistral Large 2407

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 DeepSeek V3.1 and Mistral Large 2407.

DeepSeek

DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

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Mistral

Mistral Large 2407

This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....

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Technical Specifications

SpecificationDeepSeek V3.1Mistral Large 2407
ProviderDeepSeekMistral
Context Window163,840 tokens131,072 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelself hostableself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-08-212024-11-19

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V3.1

$0.21

Mistral Large 2407

$2.00

Output Price per Million Tokens

DeepSeek V3.1

$0.79

Mistral Large 2407

$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.

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

Mistral Large 2407 Quirks & Gotchas

No developer gotchas reported.