Model comparison

GPT-5.2 Codex vs Qwen2.5-VL 72B Instruct

GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 29.9 on the Noometry Index.

Last verified . 0 shared benchmarks.

GPT-5.2 Codex OpenAI

42.6

Rank #111 Reported

Summary

  • The widest gap is in agentic & tool use, where GPT-5.2 Codex leads 41.0 to 18.6.
  • Qwen2.5-VL 72B Instruct is cheaper at $2.80 / $8.40 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
  • GPT-5.2 Codex accepts more context: 400K tokens versus 131K.
  • Qwen2.5-VL 72B Instruct has downloadable open weights; the other is API-only.

Side by side

GPT-5.2 Codex and Qwen2.5-VL 72B Instruct specifications
GPT-5.2 CodexQwen2.5-VL 72B Instruct
ProviderOpenAIAlibaba (Qwen)
Noometry Index42.629.9
Released2025-12-182024-09
WeightsProprietaryOpen
Context window400K131K
Max output128K8K
Input $ / M tokens$1.75$2.80
Output $ / M tokens$14$8.40
Results tracked56

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Category by category

Coding Not comparable

GPT-5.2 Codex: 45.5 (#71), Qwen2.5-VL 72B Instruct: —

Coding benchmarks
BenchmarkGPT-5.2 CodexQwen2.5-VL 72B Instruct
SWE-bench Verified (bash only)72.8%—
LMArena WebDev1339—
SWE-bench Multilingual66.3%—
ALE-Bench1,300—

Agentic & Tool Use GPT-5.2 Codex leads

GPT-5.2 Codex: 41.0 (#22), Qwen2.5-VL 72B Instruct: 18.6 (#144)

Agentic & Tool Use benchmarks
BenchmarkGPT-5.2 CodexQwen2.5-VL 72B Instruct
Terminal-Bench66.5%—
OSWorld—5%

Reasoning Not comparable

GPT-5.2 Codex: —, Qwen2.5-VL 72B Instruct: 20.7 (#233)

Reasoning benchmarks
BenchmarkGPT-5.2 CodexQwen2.5-VL 72B Instruct
Kagi LLM Benchmark—36%

Multimodal Not comparable

GPT-5.2 Codex: —, Qwen2.5-VL 72B Instruct: 33.5 (#97)

Multimodal benchmarks
BenchmarkGPT-5.2 CodexQwen2.5-VL 72B Instruct
LMArena Vision—1107
Video-MME—73.5%
GeoBench—62%
SpatialViz-Bench—33.3%

Frequently asked questions

Is GPT-5.2 Codex better than Qwen2.5-VL 72B Instruct?

GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 29.9 on the Noometry Index.

Which is cheaper, GPT-5.2 Codex or Qwen2.5-VL 72B Instruct?

Qwen2.5-VL 72B Instruct is cheaper. It lists at $2.80 per million input tokens and $8.40 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.

Which has the bigger context window?

GPT-5.2 Codex does, with 400K tokens against 131K.

How many benchmarks do GPT-5.2 Codex and Qwen2.5-VL 72B Instruct share?

0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.

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