Noometry

Model comparison

GPT-5-Codex vs Qwen3.5 27B

Qwen3.5 27B is the stronger model overall, scoring 41.9 to 37.9 on the Noometry Index.

Last verified . 1 shared benchmarks.

GPT-5-Codex OpenAI

37.9

Rank #192 Reported

Qwen3.5 27B Alibaba (Qwen)

41.9

Rank #127 Confirmed

Summary

  • They share 1 benchmark with published results for both. GPT-5-Codex scores higher in 2 categories and Qwen3.5 27B in 0 categories; 2 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GPT-5-Codex leads 42.4 to 38.9.
  • The biggest single-benchmark swing is WeirdML: 54.5% for GPT-5-Codex and 39.5% for Qwen3.5 27B.
  • Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
  • GPT-5-Codex accepts more context: 400K tokens versus 262K.
  • Qwen3.5 27B has downloadable open weights; the other is API-only.

Side by side

GPT-5-CodexQwen3.5 27B
ProviderOpenAIAlibaba (Qwen)
Noometry Index37.941.9
Released2025-09-152026-02-23
WeightsProprietaryOpen
Context window400K262K
Max output128K66K
Input $ / M tokens$1.25$0.30
Output $ / M tokens$10$2.40
Results tracked328

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Category by category

Coding GPT-5-Codex leads

GPT-5-Codex: 42.4 (#103), Qwen3.5 27B: 38.9 (#168)

BenchmarkGPT-5-CodexQwen3.5 27B
WeirdML54.5%39.5%
LMArena WebDev—1358
LMArena Coding—1427
ALE-Bench—349.45

Agentic & Tool Use Not comparable

GPT-5-Codex: 31.0 (#72), Qwen3.5 27B: —

BenchmarkGPT-5-CodexQwen3.5 27B
Terminal-Bench44.3%—
Vending-Bench 2—201.98

Reasoning GPT-5-Codex leads

GPT-5-Codex: 30.9 (#83), Qwen3.5 27B: 27.5 (#117)

BenchmarkGPT-5-CodexQwen3.5 27B
Kagi LLM Benchmark70.3%—
NYT Connections (extended)—47.9%
Thematic Generalization—45.5%
LMArena Hard Prompts—1414
DTBench—82.4%
LMCA—34%

Math Not comparable

GPT-5-Codex: —, Qwen3.5 27B: 38.8 (#127)

BenchmarkGPT-5-CodexQwen3.5 27B
MathArena Final-Answer Competitions—56.7%
LMArena Math—1429

Knowledge Not comparable

GPT-5-Codex: —, Qwen3.5 27B: 38.0 (#150)

BenchmarkGPT-5-CodexQwen3.5 27B
Vectara Hallucination Rate—12.1%
LMArena Expert—1428

Multimodal Not comparable

GPT-5-Codex: —, Qwen3.5 27B: 39.4 (#59)

BenchmarkGPT-5-CodexQwen3.5 27B
LMArena Vision—1241

Multilingual Not comparable

GPT-5-Codex: —, Qwen3.5 27B: 50.8 (#115)

BenchmarkGPT-5-CodexQwen3.5 27B
LMArena Non-English—1390
LMArena Chinese—1478
LMArena French—1410
LMArena German—1393
LMArena Japanese—1345
LMArena Korean—1358
LMArena Russian—1390
LMArena Spanish—1407

Instruction Following Not comparable

GPT-5-Codex: —, Qwen3.5 27B: 73.5 (#119)

BenchmarkGPT-5-CodexQwen3.5 27B
LMArena Instruction Following—1393

Long Context Not comparable

GPT-5-Codex: —, Qwen3.5 27B: 43.1 (#106)

BenchmarkGPT-5-CodexQwen3.5 27B
LMArena Longer Query—1413

Writing & Preference Not comparable

GPT-5-Codex: —, Qwen3.5 27B: 59.3 (#111)

BenchmarkGPT-5-CodexQwen3.5 27B
LMArena Text—1409
LMArena Creative Writing—1362
LMArena Multi-Turn—1410

Frequently asked questions

Is GPT-5-Codex better than Qwen3.5 27B?

Qwen3.5 27B is the stronger model overall, scoring 41.9 to 37.9 on the Noometry Index.

Which is cheaper, GPT-5-Codex or Qwen3.5 27B?

Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

Is GPT-5-Codex or Qwen3.5 27B better for coding?

GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 38.9 in the Noometry coding category.

Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 262K.

How many benchmarks do GPT-5-Codex and Qwen3.5 27B share?

1 benchmark has published results for both models. GPT-5-Codex has 3 scored results on Noometry and Qwen3.5 27B has 28.

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