Noometry

Model comparison

GPT-4.1 nano vs Mistral Small 3.2

Mistral Small 3.2 is the stronger model overall, scoring 31.2 to 27.9 on the Noometry Index.

Last verified . 5 shared benchmarks.

GPT-4.1 nano OpenAI

27.9

Rank #327 Confirmed

Mistral Small 3.2 Mistral AI

31.2

Rank #280 Confirmed

Summary

  • They share 5 benchmarks with published results for both. GPT-4.1 nano scores higher in 1 category and Mistral Small 3.2 in 3 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Mistral Small 3.2 leads 18.1 to 8.5.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 33.3% for GPT-4.1 nano and 40.4% for Mistral Small 3.2.
  • Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.10 / $0.40 for GPT-4.1 nano.
  • GPT-4.1 nano accepts more context: 1.05M tokens versus 256K.
  • Mistral Small 3.2 has downloadable open weights; the other is API-only.

Side by side

GPT-4.1 nanoMistral Small 3.2
ProviderOpenAIMistral AI
Noometry Index27.931.2
Released2025-04-142025-06-20
WeightsProprietaryOpen
Context window1.05M256K
Max output33K16K
Input $ / M tokens$0.10$0.0938
Output $ / M tokens$0.40$0.25
Results tracked386

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Category by category

Coding Not comparable

GPT-4.1 nano: 24.1 (#330), Mistral Small 3.2: —

BenchmarkGPT-4.1 nanoMistral Small 3.2
Aider Polyglot8.9%—
SciCode25.9%—
WeirdML19%—
LMArena Coding1306—

Agentic & Tool Use Not comparable

GPT-4.1 nano: 26.5 (#104), Mistral Small 3.2: —

BenchmarkGPT-4.1 nanoMistral Small 3.2
Berkeley Function Calling Leaderboard33%—

Reasoning Mistral Small 3.2 leads

GPT-4.1 nano: 8.5 (#349), Mistral Small 3.2: 18.1 (#287)

BenchmarkGPT-4.1 nanoMistral Small 3.2
Kagi LLM Benchmark33.3%40.4%
Epoch Capabilities Index129.62131.74
ARC-AGI-20%—
ARC-AGI-10%—
CritPt0%—
Chess Puzzles—1%
LMArena Hard Prompts1286—
DTBench52.5%—
LMCA5.5%—

Math Too close to call

GPT-4.1 nano: 26.9 (#252), Mistral Small 3.2: 26.3 (#260)

BenchmarkGPT-4.1 nanoMistral Small 3.2
OTIS Mock AIME 2024-202528.9%30.3%
Omni-MATH36.7%—
LMArena Math1274—
MATH Level 570%—
FrontierMath (Feb 2025 set)1%—

Knowledge Mistral Small 3.2 leads

GPT-4.1 nano: 21.8 (#273), Mistral Small 3.2: 26.7 (#256)

BenchmarkGPT-4.1 nanoMistral Small 3.2
GPQA Diamond48.9%49.1%
SimpleQA Verified6%—
MMLU-Pro55%—
GPQA (HELM)50.7%—
LMArena Expert1272—

Multimodal Not comparable

GPT-4.1 nano: 29.2 (#113), Mistral Small 3.2: —

BenchmarkGPT-4.1 nanoMistral Small 3.2
LMArena Vision1063—

Multilingual Not comparable

GPT-4.1 nano: 41.6 (#205), Mistral Small 3.2: —

BenchmarkGPT-4.1 nanoMistral Small 3.2
LMArena Non-English1260—
LMArena Chinese1270—
LMArena German1288—
LMArena Japanese1198—
LMArena Russian1261—

Instruction Following Not comparable

GPT-4.1 nano: 67.8 (#193), Mistral Small 3.2: —

BenchmarkGPT-4.1 nanoMistral Small 3.2
IFEval84.3%—
LMArena Instruction Following1267—

Long Context Not comparable

GPT-4.1 nano: 23.7 (#296), Mistral Small 3.2: —

BenchmarkGPT-4.1 nanoMistral Small 3.2
Fiction.LiveBench25%—
LMArena Longer Query1283—

Writing & Preference Mistral Small 3.2 leads

GPT-4.1 nano: 40.5 (#243), Mistral Small 3.2: 45.0 (#224)

BenchmarkGPT-4.1 nanoMistral Small 3.2
EQ-Bench Creative Writing9461255
LMArena Text1285—
LMArena Creative Writing1260—
WildBench81.2%—
LMArena Multi-Turn1277—

Frequently asked questions

Is GPT-4.1 nano better than Mistral Small 3.2?

Mistral Small 3.2 is the stronger model overall, scoring 31.2 to 27.9 on the Noometry Index.

Which is cheaper, GPT-4.1 nano 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; GPT-4.1 nano lists at $0.10 and $0.40.

Which has the bigger context window?

GPT-4.1 nano does, with 1.05M tokens against 256K.

How many benchmarks do GPT-4.1 nano and Mistral Small 3.2 share?

5 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Mistral Small 3.2 has 6.

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