Model comparison

o4-mini vs Qwen3.6 Plus

Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 41.6 on the Noometry Index.

Last verified . 30 shared benchmarks.

o4-mini OpenAI

41.6

Rank #132 Confirmed

Qwen3.6 Plus Alibaba (Qwen)

47.5

Rank #62 Confirmed

Summary

  • They share 30 benchmarks with published results for both. o4-mini scores higher in 3 categories and Qwen3.6 Plus in 5 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3.6 Plus leads 56.1 to 43.6.
  • The biggest single-benchmark swing is SimpleQA Verified: 19.6% for o4-mini and 44.1% for Qwen3.6 Plus.
  • Qwen3.6 Plus is cheaper at $0.50 / $3 per million input/output tokens, against $1.10 / $4.40 for o4-mini.
  • Qwen3.6 Plus accepts more context: 1M tokens versus 200K.

Side by side

o4-mini and Qwen3.6 Plus specifications
o4-miniQwen3.6 Plus
ProviderOpenAIAlibaba (Qwen)
Noometry Index41.647.5
Released2025-04-162026-03-31
WeightsProprietaryProprietary
Context window200K1M
Max output100K66K
Input $ / M tokens$1.10$0.50
Output $ / M tokens$4.40$3
Results tracked6037

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

Category by category

Coding Too close to call

o4-mini: 40.9 (#127), Qwen3.6 Plus: 40.8 (#130)

Coding benchmarks
Benchmarko4-miniQwen3.6 Plus
LMArena Coding13681467
ALE-Bench826.17670.15
SWE-bench Verified—57.9%
SWE-bench Verified (bash only)45%—
Aider Polyglot72%—
LMArena WebDev—1461
SciCode—40.7%
GSO3.6%—
WeirdML52.6%—
CadEval62%—
AlgoTune1.72—

Agentic & Tool Use Not comparable

o4-mini: 32.6 (#61), Qwen3.6 Plus: —

Agentic & Tool Use benchmarks
Benchmarko4-miniQwen3.6 Plus
Berkeley Function Calling Leaderboard53.2%—
GDPval25.3%—
METR Time Horizons63.9%—
Vending-Bench 2—5,115

Reasoning Qwen3.6 Plus leads

o4-mini: 24.6 (#162), Qwen3.6 Plus: 29.3 (#93)

Reasoning benchmarks
Benchmarko4-miniQwen3.6 Plus
CritPt0.6%2.9%
Chess Puzzles26%17%
LMArena Hard Prompts13511449
Mystery Game Puzzles5%12%
DTBench77.6%81.9%
LMCA26.5%33.1%
Epoch Capabilities Index145.64147.65
ARC-AGI-26.1%—
SimpleBench38.7%—
Kagi LLM Benchmark67.6%—
NYT Connections (extended)—60.3%
ARC-AGI-158.7%—
EnigmaEval9.2%—
Thematic Generalization—59.5%
ForecastBench61.8—

Math Qwen3.6 Plus leads

o4-mini: 40.8 (#89), Qwen3.6 Plus: 51.8 (#54)

Math benchmarks
Benchmarko4-miniQwen3.6 Plus
FrontierMath (Tiers 1-3)36.1%38.2%
OTIS Mock AIME 2024-202581.7%93.3%
LMArena Math13891450
FrontierMath (Feb 2025 set)24.8%26.2%
FrontierMath Tier 4 (v1)6.3%8.3%
FrontierMath Tier 44.9%—
Omni-MATH72%—
MATH Level 597.8%—

Knowledge Qwen3.6 Plus leads

o4-mini: 43.6 (#91), Qwen3.6 Plus: 56.1 (#45)

Knowledge benchmarks
Benchmarko4-miniQwen3.6 Plus
GPQA Diamond79.6%88.4%
SimpleQA Verified19.6%44.1%
LMArena Expert13431454
Humanity's Last Exam18.1%—
MMLU-Pro82%—
Confabulations15.8%—
Vectara Hallucination Rate18.6%—
GPQA (HELM)73.5%—

Multimodal Not comparable

o4-mini: 40.2 (#49), Qwen3.6 Plus: —

Multimodal benchmarks
Benchmarko4-miniQwen3.6 Plus
LMArena Vision1194—
GeoBench64%—
VPCT57.5%—

Multilingual Qwen3.6 Plus leads

o4-mini: 47.0 (#154), Qwen3.6 Plus: 53.3 (#70)

Multilingual benchmarks
Benchmarko4-miniQwen3.6 Plus
LMArena Non-English13371424
LMArena Chinese13541477
LMArena French13641455
LMArena German13361452
LMArena Japanese13081389
LMArena Korean13121379
LMArena Russian13341434
LMArena Spanish13471432

Instruction Following Too close to call

o4-mini: 75.2 (#68), Qwen3.6 Plus: 75.0 (#74)

Instruction Following benchmarks
Benchmarko4-miniQwen3.6 Plus
LMArena Instruction Following13211425
IFEval92.8%—

Long Context Too close to call

o4-mini: 45.5 (#33), Qwen3.6 Plus: 45.2 (#49)

Long Context benchmarks
Benchmarko4-miniQwen3.6 Plus
LMArena Longer Query13151439
Fiction.LiveBench77.8%—
CL-bench—20.3%

Writing & Preference Qwen3.6 Plus leads

o4-mini: 54.0 (#152), Qwen3.6 Plus: 62.2 (#82)

Writing & Preference benchmarks
Benchmarko4-miniQwen3.6 Plus
LMArena Text13531437
LMArena Creative Writing12941404
LMArena Multi-Turn13501438
Short-Story Creative Writing75%—
WildBench85.4%—

Frequently asked questions

Is o4-mini better than Qwen3.6 Plus?

Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 41.6 on the Noometry Index.

Which is cheaper, o4-mini or Qwen3.6 Plus?

Qwen3.6 Plus is cheaper. It lists at $0.50 per million input tokens and $3 per million output tokens; o4-mini lists at $1.10 and $4.40.

Is o4-mini or Qwen3.6 Plus better for coding?

They score almost the same on coding (40.9 vs 40.8); test both on your own repository before choosing.

Which has the bigger context window?

Qwen3.6 Plus does, with 1M tokens against 200K.

How many benchmarks do o4-mini and Qwen3.6 Plus share?

30 benchmarks have published results for both models. o4-mini has 60 scored results on Noometry and Qwen3.6 Plus has 37.

Related comparisons

Go deeper