Model comparison

GPT-5.2 Codex vs Qwen3.5 35B-A3B

GPT-5.2 Codex and Qwen3.5 35B-A3B score almost the same on the Noometry Index (42.2 vs 41.7), so choose on price, context window or the category you care about most.

Last verified . 1 shared benchmarks.

GPT-5.2 Codex OpenAI

42.2

Rank #107 Reported

Qwen3.5 35B-A3B Alibaba (Qwen)

41.7

Rank #118 Confirmed

Summary

  • They share 1 benchmark with published results for both. GPT-5.2 Codex scores higher in 1 category and Qwen3.5 35B-A3B in 0 categories; one gap is clear of the uncertainty.
  • The widest gap is in coding, where GPT-5.2 Codex leads 45.4 to 33.5.
  • Qwen3.5 35B-A3B is cheaper at $0.25 / $2 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.
  • Qwen3.5 35B-A3B has downloadable open weights; the other is API-only.

Side by side

GPT-5.2 Codex and Qwen3.5 35B-A3B specifications
GPT-5.2 CodexQwen3.5 35B-A3B
ProviderOpenAIAlibaba (Qwen)
Noometry Index42.241.7
Released2025-12-182026-02-01
WeightsProprietaryOpen
Context window400K262K
Max output128K66K
Input $ / M tokens$1.75$0.25
Output $ / M tokens$14$2
Results tracked528

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Category by category

Coding GPT-5.2 Codex leads

GPT-5.2 Codex: 45.4 (#66), Qwen3.5 35B-A3B: 33.5 (#244)

Coding benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
LMArena WebDev13391254
SWE-bench Verified (bash only)72.8%—
SWE-bench Multilingual66.3%—
SciCode—29.3%
LMArena Coding—1410
ALE-Bench1,300—

Agentic & Tool Use Not comparable

GPT-5.2 Codex: 40.7 (#20), Qwen3.5 35B-A3B: —

Agentic & Tool Use benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
Terminal-Bench66.5%—

Reasoning Not comparable

GPT-5.2 Codex: —, Qwen3.5 35B-A3B: 23.9 (#158)

Reasoning benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
CritPt—0.6%
Chess Puzzles—10%
LMArena Hard Prompts—1400
DTBench—80%
LMCA—29.5%
Epoch Capabilities Index—142.52

Math Not comparable

GPT-5.2 Codex: —, Qwen3.5 35B-A3B: 38.4 (#86)

Math benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
MathArena Final-Answer Competitions—56%
OTIS Mock AIME 2024-2025—70%
LMArena Math—1404

Knowledge Not comparable

GPT-5.2 Codex: —, Qwen3.5 35B-A3B: 47.7 (#73)

Knowledge benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
GPQA Diamond—83.5%
Vectara Hallucination Rate—10.5%
LMArena Expert—1408

Multilingual Not comparable

GPT-5.2 Codex: —, Qwen3.5 35B-A3B: 50.2 (#122)

Multilingual benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
LMArena Non-English—1379
LMArena Chinese—1458
LMArena French—1412
LMArena German—1367
LMArena Japanese—1326
LMArena Korean—1354
LMArena Russian—1377
LMArena Spanish—1390

Instruction Following Not comparable

GPT-5.2 Codex: —, Qwen3.5 35B-A3B: 73.0 (#123)

Instruction Following benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
LMArena Instruction Following—1379

Long Context Not comparable

GPT-5.2 Codex: —, Qwen3.5 35B-A3B: 42.4 (#122)

Long Context benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
LMArena Longer Query—1390

Writing & Preference Not comparable

GPT-5.2 Codex: —, Qwen3.5 35B-A3B: 58.1 (#118)

Writing & Preference benchmarks
BenchmarkGPT-5.2 CodexQwen3.5 35B-A3B
LMArena Text—1395
LMArena Creative Writing—1347
LMArena Multi-Turn—1391

Frequently asked questions

Is GPT-5.2 Codex better than Qwen3.5 35B-A3B?

GPT-5.2 Codex and Qwen3.5 35B-A3B score almost the same on the Noometry Index (42.2 vs 41.7), so choose on price, context window or the category you care about most.

Which is cheaper, GPT-5.2 Codex or Qwen3.5 35B-A3B?

Qwen3.5 35B-A3B is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.

Is GPT-5.2 Codex or Qwen3.5 35B-A3B better for coding?

GPT-5.2 Codex scores higher on coding benchmarks: 45.4 versus 33.5 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 Qwen3.5 35B-A3B share?

1 benchmark has published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Qwen3.5 35B-A3B has 28.

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