Model comparison

o4-mini vs Qwen1.5-7B

o4-mini is the stronger model overall, scoring 41.6 to 31.4 on the Noometry Index.

Last verified . 12 shared benchmarks.

o4-mini OpenAI

41.6

Rank #132 Confirmed

Qwen1.5-7B Alibaba (Qwen)

31.4

Rank #273 Confirmed

Summary

  • They share 12 benchmarks with published results for both. o4-mini scores higher in 8 categories and Qwen1.5-7B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where o4-mini leads 54.0 to 29.6.
  • Qwen1.5-7B has downloadable open weights; the other is API-only.

Side by side

o4-mini and Qwen1.5-7B specifications
o4-miniQwen1.5-7B
ProviderOpenAIAlibaba (Qwen)
Noometry Index41.631.4
Released2025-04-162024-02-04
WeightsProprietaryOpen
Context window200K—
Max output100K—
Input $ / M tokens$1.10—
Output $ / M tokens$4.40—
Results tracked6013

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Category by category

Coding o4-mini leads

o4-mini: 40.9 (#127), Qwen1.5-7B: 32.2 (#276)

Coding benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Coding13681107
SWE-bench Verified (bash only)45%—
Aider Polyglot72%—
GSO3.6%—
WeirdML52.6%—
CadEval62%—
ALE-Bench826.17—
AlgoTune1.72—

Agentic & Tool Use Not comparable

o4-mini: 32.6 (#61), Qwen1.5-7B: —

Agentic & Tool Use benchmarks
Benchmarko4-miniQwen1.5-7B
Berkeley Function Calling Leaderboard53.2%—
GDPval25.3%—
METR Time Horizons63.9%—

Reasoning o4-mini leads

o4-mini: 24.6 (#162), Qwen1.5-7B: 20.4 (#240)

Reasoning benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Hard Prompts13511065
ARC-AGI-26.1%—
SimpleBench38.7%—
Kagi LLM Benchmark67.6%—
ARC-AGI-158.7%—
CritPt0.6%—
Chess Puzzles26%—
EnigmaEval9.2%—
Mystery Game Puzzles5%—
DTBench77.6%—
LMCA26.5%—
Epoch Capabilities Index145.64—
ForecastBench61.8—

Math o4-mini leads

o4-mini: 40.8 (#89), Qwen1.5-7B: 31.4 (#224)

Math benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Math13891080
FrontierMath (Tiers 1-3)36.1%—
FrontierMath Tier 44.9%—
OTIS Mock AIME 2024-202581.7%—
Omni-MATH72%—
MATH Level 597.8%—
FrontierMath (Feb 2025 set)24.8%—
FrontierMath Tier 4 (v1)6.3%—

Knowledge o4-mini leads

o4-mini: 43.6 (#91), Qwen1.5-7B: 28.7 (#243)

Knowledge benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Expert13431055
GPQA Diamond79.6%—
Humanity's Last Exam18.1%—
SimpleQA Verified19.6%—
MMLU-Pro82%—
Confabulations15.8%—
Vectara Hallucination Rate18.6%—
GPQA (HELM)73.5%—
MMLU—62.6%

Multimodal Not comparable

o4-mini: 40.2 (#49), Qwen1.5-7B: —

Multimodal benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Vision1194—
GeoBench64%—
VPCT57.5%—

Multilingual o4-mini leads

o4-mini: 47.0 (#154), Qwen1.5-7B: 28.5 (#271)

Multilingual benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Non-English13371058
LMArena Chinese13541141
LMArena Russian13341006
LMArena French1364—
LMArena German1336—
LMArena Japanese1308—
LMArena Korean1312—
LMArena Spanish1347—

Instruction Following o4-mini leads

o4-mini: 75.2 (#68), Qwen1.5-7B: 54.1 (#281)

Instruction Following benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Instruction Following13211058
IFEval92.8%—

Long Context o4-mini leads

o4-mini: 45.5 (#33), Qwen1.5-7B: 33.1 (#266)

Long Context benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Longer Query13151090
Fiction.LiveBench77.8%—

Writing & Preference o4-mini leads

o4-mini: 54.0 (#152), Qwen1.5-7B: 29.6 (#293)

Writing & Preference benchmarks
Benchmarko4-miniQwen1.5-7B
LMArena Text13531083
LMArena Creative Writing12941035
LMArena Multi-Turn13501062
Short-Story Creative Writing75%—
WildBench85.4%—

Frequently asked questions

Is o4-mini better than Qwen1.5-7B?

o4-mini is the stronger model overall, scoring 41.6 to 31.4 on the Noometry Index.

Is o4-mini or Qwen1.5-7B better for coding?

o4-mini scores higher on coding benchmarks: 40.9 versus 32.2 in the Noometry coding category.

How many benchmarks do o4-mini and Qwen1.5-7B share?

12 benchmarks have published results for both models. o4-mini has 60 scored results on Noometry and Qwen1.5-7B has 13.

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