Model comparison

gpt-oss-120b vs Qwen1.5-7B

gpt-oss-120b is the stronger model overall, scoring 36.3 to 31.4 on the Noometry Index.

Last verified . 12 shared benchmarks.

gpt-oss-120b OpenAI

36.3

Rank #217 Confirmed

Qwen1.5-7B Alibaba (Qwen)

31.4

Rank #273 Confirmed

Summary

  • They share 12 benchmarks with published results for both. gpt-oss-120b scores higher in 6 categories and Qwen1.5-7B in 2 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in math, where gpt-oss-120b leads 52.5 to 31.4.

Side by side

gpt-oss-120b and Qwen1.5-7B specifications
gpt-oss-120bQwen1.5-7B
ProviderOpenAIAlibaba (Qwen)
Noometry Index36.331.4
Released2025-08-052024-02-04
WeightsOpenOpen
Context window131K—
Max output41K—
Input $ / M tokens$0.037—
Output $ / M tokens$0.17—
Results tracked4813

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Category by category

Coding gpt-oss-120b leads

gpt-oss-120b: 33.5 (#256), Qwen1.5-7B: 32.2 (#276)

Coding benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Coding13801107
SWE-bench Verified (bash only)26%—
Aider Polyglot41.8%—
SciCode36%—
WeirdML48.2%—
ALE-Bench575.62—
AlgoTune1.41—

Agentic & Tool Use Not comparable

gpt-oss-120b: 12.2 (#153), Qwen1.5-7B: —

Agentic & Tool Use benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
Terminal-Bench18.7%—
APEX-Agents4.4%—
METR Time Horizons56.6%—
Vending-Bench 2-21.53—

Reasoning Too close to call

gpt-oss-120b: 20.0 (#245), Qwen1.5-7B: 20.4 (#240)

Reasoning benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Hard Prompts13641065
SimpleBench22.1%—
Kagi LLM Benchmark58.6%—
CritPt1.1%—
Chess Puzzles20%—
Mystery Game Puzzles2%—
DTBench76.3%—
LMCA22.1%—
Surface Evolver Bench25%—
Epoch Capabilities Index139.93—

Math gpt-oss-120b leads

gpt-oss-120b: 52.5 (#50), Qwen1.5-7B: 31.4 (#224)

Math benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Math13891080
OTIS Mock AIME 2024-202588.9%—
Omni-MATH68.8%—

Knowledge gpt-oss-120b leads

gpt-oss-120b: 42.4 (#96), Qwen1.5-7B: 28.7 (#243)

Knowledge benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Expert13561055
GPQA Diamond75.8%—
MMLU-Pro79.5%—
Confabulations15.7%—
Vectara Hallucination Rate14.2%—
GPQA (HELM)68.4%—
MMLU—62.6%

Multilingual gpt-oss-120b leads

gpt-oss-120b: 48.0 (#147), Qwen1.5-7B: 28.5 (#271)

Multilingual benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Non-English13511058
LMArena Chinese13851141
LMArena Russian13431006
LMArena French1369—
LMArena German1353—
LMArena Japanese1331—
LMArena Korean1282—
LMArena Spanish1389—

Instruction Following gpt-oss-120b leads

gpt-oss-120b: 69.3 (#173), Qwen1.5-7B: 54.1 (#281)

Instruction Following benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Instruction Following13181058
IFEval83.6%—

Long Context Qwen1.5-7B leads

gpt-oss-120b: 31.4 (#278), Qwen1.5-7B: 33.1 (#266)

Long Context benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Longer Query13191090
Fiction.LiveBench44.4%—

Writing & Preference gpt-oss-120b leads

gpt-oss-120b: 46.5 (#217), Qwen1.5-7B: 29.6 (#293)

Writing & Preference benchmarks
Benchmarkgpt-oss-120bQwen1.5-7B
LMArena Text13651083
LMArena Creative Writing12751035
LMArena Multi-Turn13401062
Short-Story Creative Writing77.1%—
EQ-Bench Creative Writing961—
WildBench84.5%—

Frequently asked questions

Is gpt-oss-120b better than Qwen1.5-7B?

gpt-oss-120b is the stronger model overall, scoring 36.3 to 31.4 on the Noometry Index.

Is gpt-oss-120b or Qwen1.5-7B better for coding?

gpt-oss-120b scores higher on coding benchmarks: 33.5 versus 32.2 in the Noometry coding category.

How many benchmarks do gpt-oss-120b and Qwen1.5-7B share?

12 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Qwen1.5-7B has 13.

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