Noometry

Model comparison

GPT-4 vs Qwen3-30B-A3B

Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 29.1 on the Noometry Index.

Last verified . 24 shared benchmarks.

GPT-4 OpenAI

29.1

Rank #316 Confirmed

Qwen3-30B-A3B Alibaba (Qwen)

38.9

Rank #179 Confirmed

Summary

  • They share 24 benchmarks with published results for both. GPT-4 scores higher in 1 category and Qwen3-30B-A3B in 7 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3-30B-A3B leads 37.4 to 10.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.1% for GPT-4 and 70.3% for Qwen3-30B-A3B.
  • Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $30 / $60 for GPT-4.
  • Qwen3-30B-A3B accepts more context: 41K tokens versus 8K.
  • Qwen3-30B-A3B has downloadable open weights; the other is API-only.

Side by side

GPT-4Qwen3-30B-A3B
ProviderOpenAIAlibaba (Qwen)
Noometry Index29.138.9
Released2023-03-142025-04-28
WeightsProprietaryOpen
Context window8K41K
Max output8K16K
Input $ / M tokens$30$0.12
Output $ / M tokens$60$0.50
Results tracked3832

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Category by category

Coding Qwen3-30B-A3B leads

GPT-4: 31.6 (#283), Qwen3-30B-A3B: 37.5 (#194)

BenchmarkGPT-4Qwen3-30B-A3B
WeirdML12.4%29.8%
LMArena Coding12541416
SciCode—33.3%
BigCodeBench Instruct46%—
BigCodeBench Complete57.2%—
HumanEval+79.3%—

Agentic & Tool Use Not comparable

GPT-4: —, Qwen3-30B-A3B: 29.8 (#82)

BenchmarkGPT-4Qwen3-30B-A3B
Berkeley Function Calling Leaderboard—41.4%
METR Time Horizons36.1%—

Reasoning Qwen3-30B-A3B leads

GPT-4: 17.8 (#289), Qwen3-30B-A3B: 22.2 (#204)

BenchmarkGPT-4Qwen3-30B-A3B
Chess Puzzles4%8%
LMArena Hard Prompts12411398
DTBench62.7%69.3%
LMCA17.1%22.4%
Epoch Capabilities Index125.89139.63
Kagi LLM Benchmark—54.9%
CritPt—0.3%
Mystery Game Puzzles12%—
BIG-Bench Hard75.1%—
ForecastBench57.8—
HellaSwag95.3%—
WinoGrande87.5%—

Math Qwen3-30B-A3B leads

GPT-4: 10.8 (#309), Qwen3-30B-A3B: 37.4 (#157)

BenchmarkGPT-4Qwen3-30B-A3B
OTIS Mock AIME 2024-20251.1%70.3%
LMArena Math12691394
MathArena Final-Answer Competitions—47.8%
MATH Level 523%—
GSM8K92%—

Knowledge Qwen3-30B-A3B leads

GPT-4: 18.4 (#282), Qwen3-30B-A3B: 41.8 (#105)

BenchmarkGPT-4Qwen3-30B-A3B
GPQA Diamond35.7%70.1%
LMArena Expert12111396
Confabulations—12.3%
MMLU86.4%—
TriviaQA84.8%—

Multilingual Qwen3-30B-A3B leads

GPT-4: 40.6 (#215), Qwen3-30B-A3B: 49.5 (#132)

BenchmarkGPT-4Qwen3-30B-A3B
LMArena Non-English12461372
LMArena Chinese12421433
LMArena French12831418
LMArena German12511380
LMArena Japanese12091337
LMArena Korean11841331
LMArena Russian12511370
LMArena Spanish12611404

Instruction Following Qwen3-30B-A3B leads

GPT-4: 65.3 (#222), Qwen3-30B-A3B: 72.0 (#142)

BenchmarkGPT-4Qwen3-30B-A3B
LMArena Instruction Following12411363

Long Context GPT-4 leads

GPT-4: 37.7 (#212), Qwen3-30B-A3B: 31.0 (#283)

BenchmarkGPT-4Qwen3-30B-A3B
LMArena Longer Query12441379
Fiction.LiveBench—40.6%

Writing & Preference Qwen3-30B-A3B leads

GPT-4: 34.9 (#268), Qwen3-30B-A3B: 55.6 (#143)

BenchmarkGPT-4Qwen3-30B-A3B
LMArena Text12631384
LMArena Creative Writing12441317
LMArena Multi-Turn12571378
Short-Story Creative Writing—75.3%
EQ-Bench Creative Writing752—

Frequently asked questions

Is GPT-4 better than Qwen3-30B-A3B?

Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 29.1 on the Noometry Index.

Which is cheaper, GPT-4 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 lists at $30 and $60.

Is GPT-4 or Qwen3-30B-A3B better for coding?

Qwen3-30B-A3B scores higher on coding benchmarks: 37.5 versus 31.6 in the Noometry coding category.

Which has the bigger context window?

Qwen3-30B-A3B does, with 41K tokens against 8K.

How many benchmarks do GPT-4 and Qwen3-30B-A3B share?

24 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen3-30B-A3B has 32.

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