Noometry

Model comparison

DeepSeek V4 Flash vs Mistral Medium 3.1

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 31.5 on the Noometry Index.

Last verified . 2 shared benchmarks.

DeepSeek V4 Flash DeepSeek

53.6

Rank #32 Confirmed

Mistral Medium 3.1 Mistral AI

31.5

Rank #260 Reported

Summary

  • They share 2 benchmarks with published results for both. DeepSeek V4 Flash 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 V4 Flash leads 53.7 to 10.1.
  • The biggest single-benchmark swing is NYT Connections (extended): 89.6% for DeepSeek V4 Flash and 6.5% for Mistral Medium 3.1.
  • DeepSeek V4 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
  • DeepSeek V4 Flash accepts more context: 1M tokens versus 131K.
  • DeepSeek V4 Flash has downloadable open weights; the other is API-only.

Side by side

DeepSeek V4 FlashMistral Medium 3.1
ProviderDeepSeekMistral AI
Noometry Index53.631.5
Released2026-04-24—
WeightsOpenProprietary
Context window1M131K
Max output393K105K
Input $ / M tokens$0.15$0.40
Output $ / M tokens$0.60$2
Results tracked413

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Category by category

Coding Not comparable

DeepSeek V4 Flash: 47.6 (#56), Mistral Medium 3.1: —

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
FrontierCode18.8%—
LMArena WebDev1581—
SciCode49.9%—
WeirdML63%—
LMArena Coding1457—
ALE-Bench1,306—

Reasoning DeepSeek V4 Flash leads

DeepSeek V4 Flash: 53.7 (#25), Mistral Medium 3.1: 10.1 (#336)

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
NYT Connections (extended)89.6%6.5%
ARC-AGI-261.4%—
SimpleBench61.1%—
Kagi LLM Benchmark52.2%—
ARC-AGI-189%—
CritPt16.6%—
Chess Puzzles33%—
Thematic Generalization—20.3%
LMArena Hard Prompts1443—
Mystery Game Puzzles34%—
DTBench90.9%—
LMCA41.7%—
Epoch Capabilities Index154.51—

Math Not comparable

DeepSeek V4 Flash: 60.0 (#31), Mistral Medium 3.1: —

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
FrontierMath (Tiers 1-3)57.5%—
FrontierMath Tier 424.4%—
MathArena Final-Answer Competitions76.5%—
OTIS Mock AIME 2024-202594.4%—
ProofBench56%—
LMArena Math1427—

Knowledge Not comparable

DeepSeek V4 Flash: 55.5 (#43), Mistral Medium 3.1: —

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
GPQA Diamond91%—
SimpleQA Verified33.6%—
LMArena Expert1441—

Multilingual Not comparable

DeepSeek V4 Flash: 53.2 (#71), Mistral Medium 3.1: —

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
LMArena Non-English1420—
LMArena Chinese1467—
LMArena French1438—
LMArena German1418—
LMArena Japanese1403—
LMArena Korean1383—
LMArena Russian1428—
LMArena Spanish1437—

Instruction Following Not comparable

DeepSeek V4 Flash: 75.1 (#76), Mistral Medium 3.1: —

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
LMArena Instruction Following1421—

Long Context Not comparable

DeepSeek V4 Flash: 43.8 (#81), Mistral Medium 3.1: —

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
LMArena Longer Query1435—

Writing & Preference DeepSeek V4 Flash leads

DeepSeek V4 Flash: 64.0 (#59), Mistral Medium 3.1: 55.6 (#140)

BenchmarkDeepSeek V4 FlashMistral Medium 3.1
EQ-Bench Creative Writing15591476
LMArena Text1432—
LMArena Creative Writing1403—
LMArena Multi-Turn1449—

Frequently asked questions

Is DeepSeek V4 Flash better than Mistral Medium 3.1?

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 31.5 on the Noometry Index.

Which is cheaper, DeepSeek V4 Flash or Mistral Medium 3.1?

DeepSeek V4 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Mistral Medium 3.1 lists at $0.40 and $2.

Which has the bigger context window?

DeepSeek V4 Flash does, with 1M tokens against 131K.

How many benchmarks do DeepSeek V4 Flash and Mistral Medium 3.1 share?

2 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Mistral Medium 3.1 has 3.

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