Noometry

Model comparison

GPT-5.2 Codex vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 45.3 to 42.2 on the Noometry Index.

Last verified . 1 shared benchmarks.

GPT-5.2 Codex OpenAI

42.2

Rank #107 Reported

Qwen3.8 27B Alibaba (Qwen)

45.3

Rank #64 Confirmed

Summary

  • They share 1 benchmark with published results for both. GPT-5.2 Codex scores higher in 0 categories and Qwen3.8 27B in 1 category; one gap is clear of the uncertainty.
  • The widest gap is in coding, where Qwen3.8 27B leads 50.3 to 45.4.
  • Qwen3.8 27B is cheaper at $0.99 / $1.49 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
  • GPT-5.2 Codex accepts more context: 400K tokens versus 262K.
  • Qwen3.8 27B has downloadable open weights; the other is API-only.

Side by side

GPT-5.2 CodexQwen3.8 27B
ProviderOpenAIAlibaba (Qwen)
Noometry Index42.245.3
Released2025-12-182026-08-14
WeightsProprietaryOpen
Context window400K262K
Max output128K33K
Input $ / M tokens$1.75$0.99
Output $ / M tokens$14$1.49
Results tracked528

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Category by category

Coding Qwen3.8 27B leads

GPT-5.2 Codex: 45.4 (#66), Qwen3.8 27B: 50.3 (#42)

BenchmarkGPT-5.2 CodexQwen3.8 27B
LMArena WebDev13391592
SWE-bench Verified (bash only)72.8%—
SWE-bench Multilingual66.3%—
SciCode—46.6%
LMArena Coding—1487
ALE-Bench1,300—

Agentic & Tool Use Not comparable

GPT-5.2 Codex: 40.7 (#20), Qwen3.8 27B: —

BenchmarkGPT-5.2 CodexQwen3.8 27B
Terminal-Bench66.5%—

Reasoning Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 31.5 (#71)

BenchmarkGPT-5.2 CodexQwen3.8 27B
NYT Connections (extended)—54.5%
CritPt—5.4%
LMArena Hard Prompts—1459
DTBench—88%
LMCA—41.4%
Surface Evolver Bench—45%
Epoch Capabilities Index—149.38

Math Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 35.7 (#139)

BenchmarkGPT-5.2 CodexQwen3.8 27B
ProofBench—16%
LMArena Math—1453

Knowledge Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 40.9 (#105)

BenchmarkGPT-5.2 CodexQwen3.8 27B
LMArena Expert—1482

Multimodal Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 40.5 (#36)

BenchmarkGPT-5.2 CodexQwen3.8 27B
LMArena Vision—1270

Multilingual Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 54.0 (#54)

BenchmarkGPT-5.2 CodexQwen3.8 27B
LMArena Non-English—1431
LMArena Chinese—1504
LMArena French—1468
LMArena German—1435
LMArena Japanese—1392
LMArena Korean—1389
LMArena Russian—1421
LMArena Spanish—1444

Instruction Following Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 75.8 (#54)

BenchmarkGPT-5.2 CodexQwen3.8 27B
LMArena Instruction Following—1436

Long Context Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 44.3 (#66)

BenchmarkGPT-5.2 CodexQwen3.8 27B
LMArena Longer Query—1448

Writing & Preference Not comparable

GPT-5.2 Codex: —, Qwen3.8 27B: 65.9 (#41)

BenchmarkGPT-5.2 CodexQwen3.8 27B
LMArena Text—1441
LMArena Creative Writing—1382
EQ-Bench Creative Writing—1671
LMArena Multi-Turn—1443

Frequently asked questions

Is GPT-5.2 Codex better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 45.3 to 42.2 on the Noometry Index.

Which is cheaper, GPT-5.2 Codex or Qwen3.8 27B?

Qwen3.8 27B is cheaper. It lists at $0.99 per million input tokens and $1.49 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.

Is GPT-5.2 Codex or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.3 versus 45.4 in the Noometry coding category.

Which has the bigger context window?

GPT-5.2 Codex does, with 400K tokens against 262K.

How many benchmarks do GPT-5.2 Codex and Qwen3.8 27B share?

1 benchmark has published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Qwen3.8 27B has 28.

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