Model comparison

DeepSeek-V3.1 vs Mistral Medium 3.1

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 31.9 on the Noometry Index.

Last verified . 1 shared benchmarks.

DeepSeek-V3.1 DeepSeek

42.8

Rank #108 Confirmed

Mistral Medium 3.1 Mistral AI

31.9

Rank #266 Reported

Summary

  • They share 1 benchmark with published results for both. DeepSeek-V3.1 scores higher in 2 categories and Mistral Medium 3.1 in 0 categories; 2 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where DeepSeek-V3.1 leads 27.9 to 10.6.
  • DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
  • DeepSeek-V3.1 accepts more context: 164K tokens versus 131K.
  • DeepSeek-V3.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1 and Mistral Medium 3.1 specifications
DeepSeek-V3.1Mistral Medium 3.1
ProviderDeepSeekMistral AI
Noometry Index42.831.9
Released2025-08-21—
WeightsOpenProprietary
Context window164K131K
Max output8K105K
Input $ / M tokens$0.25$0.40
Output $ / M tokens$0.95$2
Results tracked273

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Category by category

Coding Not comparable

DeepSeek-V3.1: 40.3 (#144), Mistral Medium 3.1: —

Coding benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
WeirdML38.4%—
LMArena Coding1417—

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.9 (#110), Mistral Medium 3.1: 10.6 (#341)

Reasoning benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
SimpleBench40%—
Kagi LLM Benchmark53.2%—
NYT Connections (extended)—6.5%
Thematic Generalization—20.3%
LMArena Hard Prompts1417—
DTBench82.7%—
LMCA24.3%—
Epoch Capabilities Index139.92—
ForecastBench58—

Math Not comparable

DeepSeek-V3.1: 38.9 (#122), Mistral Medium 3.1: —

Math benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
LMArena Math1420—

Knowledge Not comparable

DeepSeek-V3.1: 43.7 (#90), Mistral Medium 3.1: —

Knowledge benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
Vectara Hallucination Rate5.5%—
LMArena Expert1405—

Multilingual Not comparable

DeepSeek-V3.1: 51.6 (#106), Mistral Medium 3.1: —

Multilingual benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
LMArena Non-English1400—
LMArena Chinese1469—
LMArena French1447—
LMArena German1411—
LMArena Japanese1378—
LMArena Korean1337—
LMArena Russian1405—
LMArena Spanish1431—

Instruction Following Not comparable

DeepSeek-V3.1: 73.9 (#110), Mistral Medium 3.1: —

Instruction Following benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
LMArena Instruction Following1400—

Long Context Not comparable

DeepSeek-V3.1: 36.3 (#232), Mistral Medium 3.1: —

Long Context benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
Fiction.LiveBench52.8%—
LMArena Longer Query1422—

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.3 (#98), Mistral Medium 3.1: 55.5 (#145)

Writing & Preference benchmarks
BenchmarkDeepSeek-V3.1Mistral Medium 3.1
EQ-Bench Creative Writing14361476
LMArena Text1420—
LMArena Creative Writing1401—
LMArena Multi-Turn1408—

Frequently asked questions

Is DeepSeek-V3.1 better than Mistral Medium 3.1?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 31.9 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1 or Mistral Medium 3.1?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Mistral Medium 3.1 lists at $0.40 and $2.

Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 131K.

How many benchmarks do DeepSeek-V3.1 and Mistral Medium 3.1 share?

1 benchmark has published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Mistral Medium 3.1 has 3.

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