Model comparison

GPT-5-Codex vs Qwen3.7 Plus

Qwen3.7 Plus is the stronger model overall, scoring 45.0 to 37.3 on the Noometry Index.

Last verified . 0 shared benchmarks.

GPT-5-Codex OpenAI

37.3

Rank #190 Reported

Qwen3.7 Plus Alibaba (Qwen)

45.0

Rank #66 Confirmed

Summary

  • The widest gap is in agentic & tool use, where GPT-5-Codex leads 30.8 to 21.2.
  • Qwen3.7 Plus is cheaper at $0.40 / $1.60 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
  • Qwen3.7 Plus accepts more context: 1M tokens versus 400K.

Side by side

GPT-5-Codex and Qwen3.7 Plus specifications
GPT-5-CodexQwen3.7 Plus
ProviderOpenAIAlibaba (Qwen)
Noometry Index37.345.0
Released2025-09-152026-06-02
WeightsProprietaryProprietary
Context window400K1M
Max output128K131K
Input $ / M tokens$1.25$0.40
Output $ / M tokens$10$1.60
Results tracked332

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Category by category

Coding GPT-5-Codex leads

GPT-5-Codex: 41.9 (#100), Qwen3.7 Plus: 36.1 (#200)

Coding benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
FrontierCode—10.2%
SciCode—45.5%
WeirdML54.5%—
LMArena Coding—1473

Agentic & Tool Use GPT-5-Codex leads

GPT-5-Codex: 30.8 (#66), Qwen3.7 Plus: 21.2 (#130)

Agentic & Tool Use benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
Terminal-Bench44.3%—
OSWorld 2.0—2.8%

Reasoning Qwen3.7 Plus leads

GPT-5-Codex: 30.0 (#80), Qwen3.7 Plus: 38.4 (#54)

Reasoning benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
Kagi LLM Benchmark70.3%—
NYT Connections (extended)—74.8%
CritPt—9.1%
Chess Puzzles—24%
LMArena Hard Prompts—1460
Mystery Game Puzzles—17%
DTBench—84%
LMCA—37.6%
Epoch Capabilities Index—147.39

Math Not comparable

GPT-5-Codex: —, Qwen3.7 Plus: 49.3 (#47)

Math benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
FrontierMath (Tiers 1-3)—34.4%
OTIS Mock AIME 2024-2025—93.3%
LMArena Math—1467

Knowledge Not comparable

GPT-5-Codex: —, Qwen3.7 Plus: 54.9 (#46)

Knowledge benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
GPQA Diamond—87.9%
LMArena Expert—1467

Multimodal Not comparable

GPT-5-Codex: —, Qwen3.7 Plus: 41.2 (#30)

Multimodal benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
LMArena Vision—1281
LMArena Document—1444

Multilingual Not comparable

GPT-5-Codex: —, Qwen3.7 Plus: 55.0 (#36)

Multilingual benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
LMArena Non-English—1445
LMArena Chinese—1510
LMArena French—1471
LMArena German—1471
LMArena Japanese—1411
LMArena Korean—1416
LMArena Russian—1457
LMArena Spanish—1453

Instruction Following Not comparable

GPT-5-Codex: —, Qwen3.7 Plus: 75.9 (#49)

Instruction Following benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
LMArena Instruction Following—1439

Long Context Not comparable

GPT-5-Codex: —, Qwen3.7 Plus: 44.5 (#61)

Long Context benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
LMArena Longer Query—1454

Writing & Preference Not comparable

GPT-5-Codex: —, Qwen3.7 Plus: 64.5 (#54)

Writing & Preference benchmarks
BenchmarkGPT-5-CodexQwen3.7 Plus
LMArena Text—1454
LMArena Creative Writing—1439
LMArena Multi-Turn—1459

Frequently asked questions

Is GPT-5-Codex better than Qwen3.7 Plus?

Qwen3.7 Plus is the stronger model overall, scoring 45.0 to 37.3 on the Noometry Index.

Which is cheaper, GPT-5-Codex or Qwen3.7 Plus?

Qwen3.7 Plus is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

Is GPT-5-Codex or Qwen3.7 Plus better for coding?

GPT-5-Codex scores higher on coding benchmarks: 41.9 versus 36.1 in the Noometry coding category.

Which has the bigger context window?

Qwen3.7 Plus does, with 1M tokens against 400K.

How many benchmarks do GPT-5-Codex and Qwen3.7 Plus share?

0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Qwen3.7 Plus has 32.

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