Noometry

Model comparison

GPT-4.1 nano vs Qwen2.5-Coder-32B

Qwen2.5-Coder-32B is the stronger model overall, scoring 33.4 to 27.9 on the Noometry Index. GPT-4.1 nano costs 4.3× less per token, which makes it the better buy when Qwen2.5-Coder-32B's lead doesn't matter for your workload.

Last verified . 14 shared benchmarks.

GPT-4.1 nano OpenAI

27.9

Rank #327 Confirmed

Qwen2.5-Coder-32B Alibaba (Qwen)

33.4

Rank #245 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GPT-4.1 nano scores higher in 3 categories and Qwen2.5-Coder-32B in 5 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in long context, where Qwen2.5-Coder-32B leads 38.0 to 23.7.
  • The biggest single-benchmark swing is Aider Polyglot: 8.9% for GPT-4.1 nano and 16.4% for Qwen2.5-Coder-32B.
  • GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.66 / $1 for Qwen2.5-Coder-32B.
  • GPT-4.1 nano accepts more context: 1.05M tokens versus 33K.
  • Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

Side by side

GPT-4.1 nanoQwen2.5-Coder-32B
ProviderOpenAIAlibaba (Qwen)
Noometry Index27.933.4
Released2025-04-142024-09-18
WeightsProprietaryOpen
Context window1.05M33K
Max output33K29K
Input $ / M tokens$0.10$0.66
Output $ / M tokens$0.40$1
Results tracked3831

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Category by category

Coding GPT-4.1 nano leads

GPT-4.1 nano: 24.1 (#330), Qwen2.5-Coder-32B: 22.6 (#333)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
Aider Polyglot8.9%16.4%
LMArena Coding13061276
SWE-bench Verified (bash only)—9%
SciCode25.9%—
WeirdML19%—
BigCodeBench Instruct—49%
LiveBench Coding—56.9%
BigCodeBench Complete—58%
HumanEval+—87.2%
MBPP+—77%

Agentic & Tool Use Not comparable

GPT-4.1 nano: 26.5 (#104), Qwen2.5-Coder-32B: —

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
Berkeley Function Calling Leaderboard33%—

Reasoning Qwen2.5-Coder-32B leads

GPT-4.1 nano: 8.5 (#349), Qwen2.5-Coder-32B: 21.2 (#225)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Hard Prompts12861251
Epoch Capabilities Index129.62119.49
ARC-AGI-20%—
Kagi LLM Benchmark33.3%—
ARC-AGI-10%—
CritPt0%—
LiveBench Reasoning—42.1%
DTBench52.5%—
LiveBench Data Analysis—49.9%
LMCA5.5%—
HellaSwag—83%
LiveBench—46.2%
WinoGrande—80.8%

Math Qwen2.5-Coder-32B leads

GPT-4.1 nano: 26.9 (#252), Qwen2.5-Coder-32B: 33.3 (#204)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Math12741251
OTIS Mock AIME 2024-202528.9%—
Omni-MATH36.7%—
LiveBench Math—46.6%
MATH Level 570%—
FrontierMath (Feb 2025 set)1%—
GSM8K—93%

Knowledge Qwen2.5-Coder-32B leads

GPT-4.1 nano: 21.8 (#273), Qwen2.5-Coder-32B: 33.4 (#203)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Expert12721221
GPQA Diamond48.9%—
SimpleQA Verified6%—
MMLU-Pro55%—
GPQA (HELM)50.7%—
ARC (AI2) Challenge—70.5%
MMLU—79.1%

Multimodal Not comparable

GPT-4.1 nano: 29.2 (#113), Qwen2.5-Coder-32B: —

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Vision1063—

Multilingual GPT-4.1 nano leads

GPT-4.1 nano: 41.6 (#205), Qwen2.5-Coder-32B: 37.8 (#235)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Non-English12601205
LMArena Chinese12701222
LMArena Russian12611228
LMArena German1288—
LMArena Japanese1198—

Instruction Following GPT-4.1 nano leads

GPT-4.1 nano: 67.8 (#193), Qwen2.5-Coder-32B: 61.4 (#245)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Instruction Following12671223
LiveBench Instruction Following—58.7%
IFEval84.3%—

Long Context Qwen2.5-Coder-32B leads

GPT-4.1 nano: 23.7 (#296), Qwen2.5-Coder-32B: 38.0 (#208)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Longer Query12831251
Fiction.LiveBench25%—

Writing & Preference Qwen2.5-Coder-32B leads

GPT-4.1 nano: 40.5 (#243), Qwen2.5-Coder-32B: 41.6 (#240)

BenchmarkGPT-4.1 nanoQwen2.5-Coder-32B
LMArena Text12851230
LMArena Creative Writing12601174
LMArena Multi-Turn12771222
EQ-Bench Creative Writing946—
WildBench81.2%—
LiveBench Language—23.3%

Frequently asked questions

Is GPT-4.1 nano better than Qwen2.5-Coder-32B?

Qwen2.5-Coder-32B is the stronger model overall, scoring 33.4 to 27.9 on the Noometry Index. GPT-4.1 nano costs 4.3× less per token, which makes it the better buy when Qwen2.5-Coder-32B's lead doesn't matter for your workload.

Which is cheaper, GPT-4.1 nano or Qwen2.5-Coder-32B?

GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Qwen2.5-Coder-32B lists at $0.66 and $1.

Is GPT-4.1 nano or Qwen2.5-Coder-32B better for coding?

GPT-4.1 nano scores higher on coding benchmarks: 24.1 versus 22.6 in the Noometry coding category.

Which has the bigger context window?

GPT-4.1 nano does, with 1.05M tokens against 33K.

How many benchmarks do GPT-4.1 nano and Qwen2.5-Coder-32B share?

14 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Qwen2.5-Coder-32B has 31.

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