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DeepSeek V3.1 vs Mistral Large 3 2512

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 3 2512.

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 3 2512

Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.

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Technical Specifications

SpecificationDeepSeek V3.1Mistral Large 3 2512
ProviderDeepSeekMistral
Context Window163,840 tokens262,144 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelself hostableself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-08-212025-12-01

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V3.1

$0.21

Mistral Large 3 2512

$0.50

Output Price per Million Tokens

DeepSeek V3.1

$0.79

Mistral Large 3 2512

$1.50

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 3 2512 Quirks & Gotchas

No developer gotchas reported.