Noometry

Model comparison

GPT-4.1 nano vs Qwen2-72B

Qwen2-72B is the stronger model overall, scoring 30.0 to 27.9 on the Noometry Index.

Last verified . 18 shared benchmarks.

GPT-4.1 nano OpenAI

27.9

Rank #327 Confirmed

Qwen2-72B Alibaba (Qwen)

30.0

Rank #300 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GPT-4.1 nano scores higher in 4 categories and Qwen2-72B in 5 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen2-72B leads 23.2 to 8.5.
  • The biggest single-benchmark swing is MATH Level 5: 70% for GPT-4.1 nano and 39.1% for Qwen2-72B.
  • Qwen2-72B has downloadable open weights; the other is API-only.

Side by side

GPT-4.1 nanoQwen2-72B
ProviderOpenAIAlibaba (Qwen)
Noometry Index27.930.0
Released2025-04-142024-06-07
WeightsProprietaryOpen
Context window1.05M—
Max output33K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.40—
Results tracked3826

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Category by category

Coding Qwen2-72B leads

GPT-4.1 nano: 24.1 (#330), Qwen2-72B: 29.1 (#310)

BenchmarkGPT-4.1 nanoQwen2-72B
WeirdML19%11.3%
LMArena Coding13061196
Aider Polyglot8.9%—
SciCode25.9%—
BigCodeBench Instruct—38.5%
BigCodeBench Complete—54%

Agentic & Tool Use GPT-4.1 nano leads

GPT-4.1 nano: 26.5 (#104), Qwen2-72B: 17.0 (#146)

BenchmarkGPT-4.1 nanoQwen2-72B
Berkeley Function Calling Leaderboard33%—
TheAgentCompany—1.1%
METR Time Horizons—29.9%

Reasoning Qwen2-72B leads

GPT-4.1 nano: 8.5 (#349), Qwen2-72B: 23.2 (#181)

BenchmarkGPT-4.1 nanoQwen2-72B
LMArena Hard Prompts12861191
Epoch Capabilities Index129.62125.28
ARC-AGI-20%—
Kagi LLM Benchmark33.3%—
ARC-AGI-10%—
CritPt0%—
DTBench52.5%—
LMCA5.5%—

Math Qwen2-72B leads

GPT-4.1 nano: 26.9 (#252), Qwen2-72B: 30.2 (#236)

BenchmarkGPT-4.1 nanoQwen2-72B
LMArena Math12741235
MATH Level 570%39.1%
OTIS Mock AIME 2024-202528.9%—
Omni-MATH36.7%—
FrontierMath (Feb 2025 set)1%—

Knowledge Too close to call

GPT-4.1 nano: 21.8 (#273), Qwen2-72B: 21.2 (#275)

BenchmarkGPT-4.1 nanoQwen2-72B
GPQA Diamond48.9%40.8%
LMArena Expert12721171
SimpleQA Verified6%—
MMLU-Pro55%—
GPQA (HELM)50.7%—
MMLU—82.4%

Multimodal Not comparable

GPT-4.1 nano: 29.2 (#113), Qwen2-72B: —

BenchmarkGPT-4.1 nanoQwen2-72B
LMArena Vision1063—

Multilingual GPT-4.1 nano leads

GPT-4.1 nano: 41.6 (#205), Qwen2-72B: 35.9 (#244)

BenchmarkGPT-4.1 nanoQwen2-72B
LMArena Non-English12601176
LMArena Chinese12701240
LMArena German12881151
LMArena Japanese11981111
LMArena Russian12611169
LMArena French—1170
LMArena Korean—1083
LMArena Spanish—1169

Instruction Following GPT-4.1 nano leads

GPT-4.1 nano: 67.8 (#193), Qwen2-72B: 61.7 (#241)

BenchmarkGPT-4.1 nanoQwen2-72B
LMArena Instruction Following12671181
IFEval84.3%—

Long Context Qwen2-72B leads

GPT-4.1 nano: 23.7 (#296), Qwen2-72B: 36.1 (#235)

BenchmarkGPT-4.1 nanoQwen2-72B
LMArena Longer Query12831192
Fiction.LiveBench25%—

Writing & Preference Too close to call

GPT-4.1 nano: 40.5 (#243), Qwen2-72B: 40.8 (#241)

BenchmarkGPT-4.1 nanoQwen2-72B
LMArena Text12851203
LMArena Creative Writing12601181
LMArena Multi-Turn12771196
EQ-Bench Creative Writing946—
WildBench81.2%—

Frequently asked questions

Is GPT-4.1 nano better than Qwen2-72B?

Qwen2-72B is the stronger model overall, scoring 30.0 to 27.9 on the Noometry Index.

Is GPT-4.1 nano or Qwen2-72B better for coding?

Qwen2-72B scores higher on coding benchmarks: 29.1 versus 24.1 in the Noometry coding category.

How many benchmarks do GPT-4.1 nano and Qwen2-72B share?

18 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Qwen2-72B has 26.

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