Noometry

Model comparison

DeepSeek V4.1 Flash vs Mistral Small 3.2

DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 2.0× less per token, which makes it the better buy when DeepSeek V4.1 Flash's lead doesn't matter for your workload.

Last verified . 2 shared benchmarks.

DeepSeek V4.1 Flash DeepSeek

50.3

Rank #40 Confirmed

Mistral Small 3.2 Mistral AI

30.8

Rank #271 Confirmed

Summary

  • They share 2 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 4 categories and Mistral Small 3.2 in 0 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where DeepSeek V4.1 Flash leads 46.2 to 17.5.
  • Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.15 / $0.60 for DeepSeek V4.1 Flash.
  • DeepSeek V4.1 Flash accepts more context: 1M tokens versus 256K.

Side by side

DeepSeek V4.1 FlashMistral Small 3.2
ProviderDeepSeekMistral AI
Noometry Index50.330.8
Released2026-09-092025-06-20
WeightsOpenOpen
Context window1M256K
Max output393K16K
Input $ / M tokens$0.15$0.0938
Output $ / M tokens$0.60$0.25
Results tracked256

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Not comparable

DeepSeek V4.1 Flash: 52.8 (#29), Mistral Small 3.2: —

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
LMArena WebDev1620—
SciCode51.9%—
LMArena Coding1511—
ALE-Bench1,092—

Reasoning DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 46.2 (#39), Mistral Small 3.2: 17.5 (#282)

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
Epoch Capabilities Index155.01131.73
Kagi LLM Benchmark—40.4%
NYT Connections (extended)89.6%—
CritPt14.3%—
Chess Puzzles—1%
LMArena Hard Prompts1485—
DTBench89.9%—
LMCA47%—
Surface Evolver Bench46.3%—

Math DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 48.4 (#52), Mistral Small 3.2: 24.9 (#251)

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
OTIS Mock AIME 2024-2025—30.3%
ProofBench54%—
LMArena Math1493—

Knowledge DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 41.6 (#97), Mistral Small 3.2: 26.8 (#249)

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
GPQA Diamond—49.1%
LMArena Expert1505—

Multilingual Not comparable

DeepSeek V4.1 Flash: 55.5 (#29), Mistral Small 3.2: —

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
LMArena Non-English1452—
LMArena Chinese1506—
LMArena French1448—
LMArena Russian1473—
LMArena Spanish1499—

Instruction Following Not comparable

DeepSeek V4.1 Flash: 77.6 (#24), Mistral Small 3.2: —

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
LMArena Instruction Following1475—

Long Context Not comparable

DeepSeek V4.1 Flash: 45.2 (#46), Mistral Small 3.2: —

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
LMArena Longer Query1476—

Writing & Preference DeepSeek V4.1 Flash leads

DeepSeek V4.1 Flash: 65.8 (#43), Mistral Small 3.2: 45.1 (#219)

BenchmarkDeepSeek V4.1 FlashMistral Small 3.2
EQ-Bench Creative Writing15401255
LMArena Text1465—
LMArena Creative Writing1436—
LMArena Multi-Turn1460—

Frequently asked questions

Is DeepSeek V4.1 Flash better than Mistral Small 3.2?

DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 2.0× less per token, which makes it the better buy when DeepSeek V4.1 Flash's lead doesn't matter for your workload.

Which is cheaper, DeepSeek V4.1 Flash or Mistral Small 3.2?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; DeepSeek V4.1 Flash lists at $0.15 and $0.60.

Which has the bigger context window?

DeepSeek V4.1 Flash does, with 1M tokens against 256K.

How many benchmarks do DeepSeek V4.1 Flash and Mistral Small 3.2 share?

2 benchmarks have published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and Mistral Small 3.2 has 6.

Related comparisons

Go deeper