Noometry

Model comparison

GPT-4.1 mini vs Qwen3-30B-A3B

Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 33.6 on the Noometry Index.

Last verified . 29 shared benchmarks.

GPT-4.1 mini OpenAI

33.6

Rank #240 Confirmed

Qwen3-30B-A3B Alibaba (Qwen)

38.9

Rank #179 Confirmed

Summary

  • They share 29 benchmarks with published results for both. GPT-4.1 mini scores higher in 3 categories and Qwen3-30B-A3B in 6 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3-30B-A3B leads 37.4 to 24.1.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 44.7% for GPT-4.1 mini and 70.3% for Qwen3-30B-A3B.
  • Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
  • GPT-4.1 mini accepts more context: 1.05M tokens versus 41K.
  • Qwen3-30B-A3B has downloadable open weights; the other is API-only.

Side by side

GPT-4.1 miniQwen3-30B-A3B
ProviderOpenAIAlibaba (Qwen)
Noometry Index33.638.9
Released2025-04-142025-04-28
WeightsProprietaryOpen
Context window1.05M41K
Max output33K16K
Input $ / M tokens$0.40$0.12
Output $ / M tokens$1.60$0.50
Results tracked4732

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Category by category

Coding Qwen3-30B-A3B leads

GPT-4.1 mini: 30.6 (#293), Qwen3-30B-A3B: 37.5 (#194)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
SciCode40.4%33.3%
WeirdML37.6%29.8%
LMArena Coding13671416
SWE-bench Verified (bash only)23.9%—
Aider Polyglot32.4%—
BigCodeBench Instruct48.9%—
CadEval16%—

Agentic & Tool Use GPT-4.1 mini leads

GPT-4.1 mini: 33.3 (#55), Qwen3-30B-A3B: 29.8 (#82)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
Berkeley Function Calling Leaderboard50.5%41.4%

Reasoning Qwen3-30B-A3B leads

GPT-4.1 mini: 10.8 (#340), Qwen3-30B-A3B: 22.2 (#204)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
Kagi LLM Benchmark48.6%54.9%
CritPt0%0.3%
Chess Puzzles7%8%
LMArena Hard Prompts13491398
DTBench68.8%69.3%
LMCA21.1%22.4%
Epoch Capabilities Index135.01139.63
ARC-AGI-20%—
ARC-AGI-13.5%—
Mystery Game Puzzles7%—

Math Qwen3-30B-A3B leads

GPT-4.1 mini: 24.1 (#270), Qwen3-30B-A3B: 37.4 (#157)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
OTIS Mock AIME 2024-202544.7%70.3%
LMArena Math13431394
FrontierMath (Tiers 1-3)6.7%—
MathArena Final-Answer Competitions—47.8%
Omni-MATH49.1%—
MATH Level 587.3%—
FrontierMath (Feb 2025 set)4.5%—

Knowledge Qwen3-30B-A3B leads

GPT-4.1 mini: 34.7 (#194), Qwen3-30B-A3B: 41.8 (#105)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
GPQA Diamond65.8%70.1%
LMArena Expert13381396
SimpleQA Verified12.7%—
MMLU-Pro78.3%—
Confabulations—12.3%
GPQA (HELM)61.4%—

Multimodal Not comparable

GPT-4.1 mini: 35.8 (#82), Qwen3-30B-A3B: —

BenchmarkGPT-4.1 miniQwen3-30B-A3B
LMArena Vision1181—

Multilingual Qwen3-30B-A3B leads

GPT-4.1 mini: 45.7 (#166), Qwen3-30B-A3B: 49.5 (#132)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
LMArena Non-English13181372
LMArena Chinese13291433
LMArena French13581418
LMArena German13511380
LMArena Japanese12901337
LMArena Korean12981331
LMArena Russian13241370
LMArena Spanish13191404

Instruction Following GPT-4.1 mini leads

GPT-4.1 mini: 73.7 (#118), Qwen3-30B-A3B: 72.0 (#142)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
LMArena Instruction Following13331363
IFEval90.4%—

Long Context Too close to call

GPT-4.1 mini: 31.8 (#275), Qwen3-30B-A3B: 31.0 (#283)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
Fiction.LiveBench44.4%40.6%
LMArena Longer Query13441379

Writing & Preference Qwen3-30B-A3B leads

GPT-4.1 mini: 48.6 (#199), Qwen3-30B-A3B: 55.6 (#143)

BenchmarkGPT-4.1 miniQwen3-30B-A3B
LMArena Text13401384
LMArena Creative Writing13001317
LMArena Multi-Turn13541378
Short-Story Creative Writing—75.3%
EQ-Bench Creative Writing1147—
WildBench83.8%—

Frequently asked questions

Is GPT-4.1 mini better than Qwen3-30B-A3B?

Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 33.6 on the Noometry Index.

Which is cheaper, GPT-4.1 mini or Qwen3-30B-A3B?

Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.

Is GPT-4.1 mini or Qwen3-30B-A3B better for coding?

Qwen3-30B-A3B scores higher on coding benchmarks: 37.5 versus 30.6 in the Noometry coding category.

Which has the bigger context window?

GPT-4.1 mini does, with 1.05M tokens against 41K.

How many benchmarks do GPT-4.1 mini and Qwen3-30B-A3B share?

29 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Qwen3-30B-A3B has 32.

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