DeepSeek V3.1 vs Mistral Large 25.12
Side-by-side benchmark comparison across coding, math, reasoning, speed, and pricing.
DeepSeek V3.1 by DeepSeek wins on 10 of 15 benchmarks against Mistral Large 25.12 by Mistral, which leads on 5. This head-to-head comparison covers coding, math, reasoning, speed, and pricing metrics from our benchmark data.
Category-by-Category Breakdown
General Intelligence: In general intelligence, Mistral Large 25.12 scores 1418 on Chatbot Arena ELO compared to DeepSeek V3.1's 1340, while DeepSeek V3.1 scores 78.0% on MMLU-Pro compared to Mistral Large 25.12's 73.0%.
Coding: In coding, DeepSeek V3.1 scores 84.0% on HumanEval+ compared to Mistral Large 25.12's 82.0%, while DeepSeek V3.1 scores 46.0% on SWE-bench Verified compared to Mistral Large 25.12's 42.0%, while DeepSeek V3.1 scores 48.0% on LiveCodeBench compared to Mistral Large 25.12's 44.0%.
Math: In math, DeepSeek V3.1 scores 82.0% on MATH compared to Mistral Large 25.12's 78.0%, while DeepSeek V3.1 scores 92.0% on GSM8K compared to Mistral Large 25.12's 91.0%.
Reasoning: In reasoning, DeepSeek V3.1 scores 55.0% on GPQA Diamond compared to Mistral Large 25.12's 52.0%, while DeepSeek V3.1 scores 35.0% on ARC-AGI compared to Mistral Large 25.12's 28.0%.
Context: In context, Mistral Large 25.12 scores 262K on Context Length compared to DeepSeek V3.1's 164K.
Pricing Comparison
DeepSeek V3.1 costs $0.25/1M input tokens and $0.95/1M output tokens, while Mistral Large 25.12 costs $0.50/1M input and $1.5/1M output. DeepSeek V3.1 is the more affordable option for API usage.
Speed Comparison
DeepSeek V3.1 generates output at 65 tok/s compared to Mistral Large 25.12's 70 tok/s, and the time to first token is 450 ms for DeepSeek V3.1 versus 380 ms for Mistral Large 25.12. Mistral Large 25.12 delivers faster throughput.
Verdict
For developers prioritizing coding and math and affordability, DeepSeek V3.1 has the edge. For those who value general intelligence and speed, Mistral Large 25.12 is the stronger choice.
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DeepSeek V3.1 vs Mistral Large 25.12 — FAQ
Which is better, DeepSeek V3.1 or Mistral Large 25.12?
DeepSeek V3.1 wins on more benchmarks overall (10 vs 5). However, the best choice depends on your specific needs — each model excels in different areas.
How does DeepSeek V3.1 compare to Mistral Large 25.12 for coding?
DeepSeek V3.1 is better for coding, scoring 46.0% on SWE-bench Verified compared to 42.0%. SWE-bench tests real-world software engineering by resolving actual GitHub issues.
Is DeepSeek V3.1 cheaper than Mistral Large 25.12?
Yes, DeepSeek V3.1 is cheaper. DeepSeek V3.1 costs $0.25/1M input and $0.95/1M output tokens. Mistral Large 25.12 costs $0.50/1M input and $1.5/1M output tokens.
Which is faster, DeepSeek V3.1 or Mistral Large 25.12?
Mistral Large 25.12 is faster, generating output at 70 tok/s compared to 65 tok/s. Faster output speed means shorter wait times for API responses.
What benchmarks does the DeepSeek V3.1 vs Mistral Large 25.12 comparison cover?
This comparison covers 15 benchmarks including Chatbot Arena ELO, MMLU-Pro, HumanEval+, MATH, GPQA Diamond, SWE-bench Verified, Output Speed, LiveCodeBench, and more. Metrics span general intelligence, coding, math, reasoning, speed, and cost categories.