Noometry

Model comparison

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

GPT-4.1 mini and Qwen2.5-Coder-32B score almost the same on the Noometry Index (33.6 vs 33.4), so choose on price, context window or the category you care about most.

Last verified . 16 shared benchmarks.

GPT-4.1 mini OpenAI

33.6

Rank #240 Confirmed

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

33.4

Rank #245 Confirmed

Summary

  • They share 16 benchmarks with published results for both. GPT-4.1 mini scores higher in 5 categories and Qwen2.5-Coder-32B in 3 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in instruction following, where GPT-4.1 mini leads 73.7 to 61.4.
  • The biggest single-benchmark swing is Aider Polyglot: 32.4% for GPT-4.1 mini and 16.4% for Qwen2.5-Coder-32B.
  • GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $0.66 / $1 for Qwen2.5-Coder-32B.
  • GPT-4.1 mini 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 miniQwen2.5-Coder-32B
ProviderOpenAIAlibaba (Qwen)
Noometry Index33.633.4
Released2025-04-142024-09-18
WeightsProprietaryOpen
Context window1.05M33K
Max output33K29K
Input $ / M tokens$0.40$0.66
Output $ / M tokens$1.60$1
Results tracked4731

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Category by category

Coding GPT-4.1 mini leads

GPT-4.1 mini: 30.6 (#293), Qwen2.5-Coder-32B: 22.6 (#333)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
SWE-bench Verified (bash only)23.9%9%
Aider Polyglot32.4%16.4%
BigCodeBench Instruct48.9%49%
LMArena Coding13671276
SciCode40.4%—
WeirdML37.6%—
LiveBench Coding—56.9%
BigCodeBench Complete—58%
CadEval16%—
HumanEval+—87.2%
MBPP+—77%

Agentic & Tool Use Not comparable

GPT-4.1 mini: 33.3 (#55), Qwen2.5-Coder-32B: —

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
Berkeley Function Calling Leaderboard50.5%—

Reasoning Qwen2.5-Coder-32B leads

GPT-4.1 mini: 10.8 (#340), Qwen2.5-Coder-32B: 21.2 (#225)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Hard Prompts13491251
Epoch Capabilities Index135.01119.49
ARC-AGI-20%—
Kagi LLM Benchmark48.6%—
ARC-AGI-13.5%—
CritPt0%—
Chess Puzzles7%—
LiveBench Reasoning—42.1%
Mystery Game Puzzles7%—
DTBench68.8%—
LiveBench Data Analysis—49.9%
LMCA21.1%—
HellaSwag—83%
LiveBench—46.2%
WinoGrande—80.8%

Math Qwen2.5-Coder-32B leads

GPT-4.1 mini: 24.1 (#270), Qwen2.5-Coder-32B: 33.3 (#204)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Math13431251
FrontierMath (Tiers 1-3)6.7%—
OTIS Mock AIME 2024-202544.7%—
Omni-MATH49.1%—
LiveBench Math—46.6%
MATH Level 587.3%—
FrontierMath (Feb 2025 set)4.5%—
GSM8K—93%

Knowledge GPT-4.1 mini leads

GPT-4.1 mini: 34.7 (#194), Qwen2.5-Coder-32B: 33.4 (#203)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Expert13381221
GPQA Diamond65.8%—
SimpleQA Verified12.7%—
MMLU-Pro78.3%—
GPQA (HELM)61.4%—
ARC (AI2) Challenge—70.5%
MMLU—79.1%

Multimodal Not comparable

GPT-4.1 mini: 35.8 (#82), Qwen2.5-Coder-32B: —

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Vision1181—

Multilingual GPT-4.1 mini leads

GPT-4.1 mini: 45.7 (#166), Qwen2.5-Coder-32B: 37.8 (#235)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Non-English13181205
LMArena Chinese13291222
LMArena Russian13241228
LMArena French1358—
LMArena German1351—
LMArena Japanese1290—
LMArena Korean1298—
LMArena Spanish1319—

Instruction Following GPT-4.1 mini leads

GPT-4.1 mini: 73.7 (#118), Qwen2.5-Coder-32B: 61.4 (#245)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Instruction Following13331223
LiveBench Instruction Following—58.7%
IFEval90.4%—

Long Context Qwen2.5-Coder-32B leads

GPT-4.1 mini: 31.8 (#275), Qwen2.5-Coder-32B: 38.0 (#208)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Longer Query13441251
Fiction.LiveBench44.4%—

Writing & Preference GPT-4.1 mini leads

GPT-4.1 mini: 48.6 (#199), Qwen2.5-Coder-32B: 41.6 (#240)

BenchmarkGPT-4.1 miniQwen2.5-Coder-32B
LMArena Text13401230
LMArena Creative Writing13001174
LMArena Multi-Turn13541222
EQ-Bench Creative Writing1147—
WildBench83.8%—
LiveBench Language—23.3%

Frequently asked questions

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

GPT-4.1 mini and Qwen2.5-Coder-32B score almost the same on the Noometry Index (33.6 vs 33.4), so choose on price, context window or the category you care about most.

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

GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; Qwen2.5-Coder-32B lists at $0.66 and $1.

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

GPT-4.1 mini scores higher on coding benchmarks: 30.6 versus 22.6 in the Noometry coding category.

Which has the bigger context window?

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

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

16 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Qwen2.5-Coder-32B has 31.

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