Noometry

Model comparison

gpt-oss-20b vs Mistral Small 3.2

gpt-oss-20b is the stronger model overall, scoring 32.5 to 31.2 on the Noometry Index.

Last verified . 6 shared benchmarks.

gpt-oss-20b OpenAI

32.5

Rank #255 Confirmed

Mistral Small 3.2 Mistral AI

31.2

Rank #280 Confirmed

Summary

  • They share 6 benchmarks with published results for both. gpt-oss-20b scores higher in 3 categories and Mistral Small 3.2 in 1 category; 4 gaps are clear of the uncertainty.
  • The widest gap is in math, where gpt-oss-20b leads 39.4 to 26.3.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 65.3% for gpt-oss-20b and 30.3% for Mistral Small 3.2.
  • gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.0938 / $0.25 for Mistral Small 3.2.
  • Mistral Small 3.2 accepts more context: 256K tokens versus 131K.

Side by side

gpt-oss-20bMistral Small 3.2
ProviderOpenAIMistral AI
Noometry Index32.531.2
Released2025-08-052025-06-20
WeightsOpenOpen
Context window131K256K
Max output16K16K
Input $ / M tokens$0.018$0.0938
Output $ / M tokens$0.09$0.25
Results tracked346

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Category by category

Coding Not comparable

gpt-oss-20b: 37.6 (#192), Mistral Small 3.2: —

Benchmarkgpt-oss-20bMistral Small 3.2
SciCode34.4%—
WeirdML40.9%—
LMArena Coding1306—
ALE-Bench566.05—

Agentic & Tool Use Not comparable

gpt-oss-20b: 9.3 (#154), Mistral Small 3.2: —

Benchmarkgpt-oss-20bMistral Small 3.2
Terminal-Bench3.4%—

Reasoning gpt-oss-20b leads

gpt-oss-20b: 19.3 (#261), Mistral Small 3.2: 18.1 (#287)

Benchmarkgpt-oss-20bMistral Small 3.2
Kagi LLM Benchmark53.2%40.4%
Chess Puzzles4%1%
Epoch Capabilities Index137.82131.74
CritPt1.4%—
LMArena Hard Prompts1274—
DTBench68%—
LMCA14.5%—

Math gpt-oss-20b leads

gpt-oss-20b: 39.4 (#103), Mistral Small 3.2: 26.3 (#260)

Benchmarkgpt-oss-20bMistral Small 3.2
OTIS Mock AIME 2024-202565.3%30.3%
Omni-MATH56.5%—
LMArena Math1317—

Knowledge gpt-oss-20b leads

gpt-oss-20b: 34.6 (#195), Mistral Small 3.2: 26.7 (#256)

Benchmarkgpt-oss-20bMistral Small 3.2
GPQA Diamond60.8%49.1%
MMLU-Pro74%—
GPQA (HELM)59.4%—
LMArena Expert1258—

Multilingual Not comparable

gpt-oss-20b: 42.2 (#197), Mistral Small 3.2: —

Benchmarkgpt-oss-20bMistral Small 3.2
LMArena Non-English1268—
LMArena Chinese1314—
LMArena German1255—
LMArena Japanese1244—
LMArena Korean1236—
LMArena Russian1278—
LMArena Spanish1267—

Instruction Following Not comparable

gpt-oss-20b: 61.8 (#240), Mistral Small 3.2: —

Benchmarkgpt-oss-20bMistral Small 3.2
IFEval73.2%—
LMArena Instruction Following1236—

Long Context Not comparable

gpt-oss-20b: 37.9 (#209), Mistral Small 3.2: —

Benchmarkgpt-oss-20bMistral Small 3.2
LMArena Longer Query1250—

Writing & Preference Mistral Small 3.2 leads

gpt-oss-20b: 35.5 (#265), Mistral Small 3.2: 45.0 (#224)

Benchmarkgpt-oss-20bMistral Small 3.2
EQ-Bench Creative Writing6661255
LMArena Text1287—
LMArena Creative Writing1201—
WildBench73.7%—
LMArena Multi-Turn1268—

Frequently asked questions

Is gpt-oss-20b better than Mistral Small 3.2?

gpt-oss-20b is the stronger model overall, scoring 32.5 to 31.2 on the Noometry Index.

Which is cheaper, gpt-oss-20b or Mistral Small 3.2?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Mistral Small 3.2 lists at $0.0938 and $0.25.

Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 131K.

How many benchmarks do gpt-oss-20b and Mistral Small 3.2 share?

6 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Mistral Small 3.2 has 6.

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