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Which is better, GPT-5.2 or Qwen3.5 122B A10B?
Across 42 shared benchmarks, GPT-5.2 scores higher on 32 and Qwen3.5 122B A10B on 10. The widest gap is OmniScience Non-Hallucination, where GPT-5.2 scores 38.4 against 12.9. Qwen3.5 122B A10B is the cheaper of the two on tracked API pricing ($0.40 against $1.75 per million input tokens).

GPT-5.2 vs Qwen3.5 122B A10B

Across 42 shared benchmarks, GPT-5.2 scores higher on 32 and Qwen3.5 122B A10B on 10. The widest gap is OmniScience Non-Hallucination, where GPT-5.2 scores 38.4 against 12.9. Qwen3.5 122B A10B is the cheaper of the two on tracked API pricing ($0.40 against $1.75 per million input tokens).

OpenAIvsAlibaba42 shared benchmarks3210 head-to-head
BenchmarkGPT-5.2Qwen3.5 122B A10B
AA Agentic Index60.221.3
AA Intelligence43.332.8
AA-LCR79.370.3
AA-Omniscience0.3-41.5
arena_vision12451246
Artificial Analysis Coding Index48.745.7
browsecomp65.863.8
browsecomp_zh76.169.9
coding_arena_elo14181358
critpt11.60.9
gdpval48.324.3
GPQA Diamond92.486.6
HLE45.547.5
HMMT 202599.490.3
IFBench75.476.1
longbench_v254.560.2
mathvision8386.2
MathVista82.887.4
MMLU-Pro8786.7
mmmlu89.686.7
MMMU-Pro79.576.9
MMVU80.874.7
OCRBench80.792.1
OmniDocBench 1.585.789.8
OmniScience Accuracy44.324.4
OmniScience Non-Hallucination38.412.9
scicode52.142
screenspot_pro_no_tools86.370.4
Seal-04544.1
SimpleVQA55.80.6
SWE-bench Verified8072
TauBench V3 - Banking11.115.3
Terminal-Bench 2.05449.4
Terminal-Bench Hard62.231.1
vectara_answer_rate10099.8
vectara_avg_summary_length186.386.4
vectara_factual_consistency89.288.8
vectara_hallucination_rate10.811.2
VideoMMMU85.982
ZeroBench90.1
τ²-Bench Telecom (AA run)98.793.6
τ³-Bench1213.6

Best tracked score per model per benchmark (default configuration; source-attributed). ↓ marks lower-is-better metrics. Open either model for its full surface, provenance and pricing. Quoted rates are the price-setter row we currently track for each model — its direct or vendor-official listing where one exists (direct, direct), otherwise the lowest tracked offer.