Model comparison

GPT-5-Codex vs Qwen3-30B-A3B

Qwen3-30B-A3B is the stronger model overall, scoring 38.5 to 37.3 on the Noometry Index.

Last verified . 2 shared benchmarks.

GPT-5-Codex OpenAI

37.3

Rank #190 Reported

Qwen3-30B-A3B Alibaba (Qwen)

38.5

Rank #174 Confirmed

Summary

  • They share 2 benchmarks with published results for both. GPT-5-Codex scores higher in 3 categories and Qwen3-30B-A3B in 0 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GPT-5-Codex leads 30.0 to 21.6.
  • The biggest single-benchmark swing is WeirdML: 54.5% for GPT-5-Codex and 29.8% for Qwen3-30B-A3B.
  • Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
  • GPT-5-Codex accepts more context: 400K tokens versus 41K.
  • Qwen3-30B-A3B has downloadable open weights; the other is API-only.

Side by side

GPT-5-Codex and Qwen3-30B-A3B specifications
GPT-5-CodexQwen3-30B-A3B
ProviderOpenAIAlibaba (Qwen)
Noometry Index37.338.5
Released2025-09-152025-04-28
WeightsProprietaryOpen
Context window400K41K
Max output128K16K
Input $ / M tokens$1.25$0.12
Output $ / M tokens$10$0.50
Results tracked332

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Category by category

Coding GPT-5-Codex leads

GPT-5-Codex: 41.9 (#100), Qwen3-30B-A3B: 37.0 (#188)

Coding benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
WeirdML54.5%29.8%
SciCode—33.3%
LMArena Coding—1416

Agentic & Tool Use GPT-5-Codex leads

GPT-5-Codex: 30.8 (#66), Qwen3-30B-A3B: 29.5 (#75)

Agentic & Tool Use benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
Terminal-Bench44.3%—
Berkeley Function Calling Leaderboard—41.4%

Reasoning GPT-5-Codex leads

GPT-5-Codex: 30.0 (#80), Qwen3-30B-A3B: 21.6 (#193)

Reasoning benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
Kagi LLM Benchmark70.3%54.9%
CritPt—0.3%
Chess Puzzles—8%
LMArena Hard Prompts—1398
DTBench—69.3%
LMCA—22.4%
Epoch Capabilities Index—139.63

Math Not comparable

GPT-5-Codex: —, Qwen3-30B-A3B: 36.0 (#133)

Math benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
MathArena Final-Answer Competitions—47.8%
OTIS Mock AIME 2024-2025—70.3%
LMArena Math—1394

Knowledge Not comparable

GPT-5-Codex: —, Qwen3-30B-A3B: 41.7 (#96)

Knowledge benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
GPQA Diamond—70.1%
Confabulations—12.3%
LMArena Expert—1395

Multilingual Not comparable

GPT-5-Codex: —, Qwen3-30B-A3B: 49.8 (#126)

Multilingual benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
LMArena Non-English—1372
LMArena Chinese—1434
LMArena French—1419
LMArena German—1379
LMArena Japanese—1338
LMArena Korean—1333
LMArena Russian—1369
LMArena Spanish—1403

Instruction Following Not comparable

GPT-5-Codex: —, Qwen3-30B-A3B: 72.2 (#137)

Instruction Following benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
LMArena Instruction Following—1364

Long Context Not comparable

GPT-5-Codex: —, Qwen3-30B-A3B: 31.0 (#278)

Long Context benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
Fiction.LiveBench—40.6%
LMArena Longer Query—1379

Writing & Preference Not comparable

GPT-5-Codex: —, Qwen3-30B-A3B: 55.9 (#138)

Writing & Preference benchmarks
BenchmarkGPT-5-CodexQwen3-30B-A3B
LMArena Text—1384
LMArena Creative Writing—1318
Short-Story Creative Writing—75.3%
LMArena Multi-Turn—1378

Frequently asked questions

Is GPT-5-Codex better than Qwen3-30B-A3B?

Qwen3-30B-A3B is the stronger model overall, scoring 38.5 to 37.3 on the Noometry Index.

Which is cheaper, GPT-5-Codex 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-5-Codex lists at $1.25 and $10.

Is GPT-5-Codex or Qwen3-30B-A3B better for coding?

GPT-5-Codex scores higher on coding benchmarks: 41.9 versus 37.0 in the Noometry coding category.

Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 41K.

How many benchmarks do GPT-5-Codex and Qwen3-30B-A3B share?

2 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Qwen3-30B-A3B has 32.

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