Model comparison
GPT-5 Pro vs Qwen1.5-32B
GPT-5 Pro is the stronger model overall, scoring 46.2 to 30.0 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where GPT-5 Pro leads 56.2 to 13.5.
- Qwen1.5-32B has downloadable open weights; the other is API-only.
Side by side
| GPT-5 Pro | Qwen1.5-32B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 46.2 | 30.0 |
| Released | 2025-10-06 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 400K | — |
| Max output | 272K | — |
| Input $ / M tokens | $15 | — |
| Output $ / M tokens | $120 | — |
| Results tracked | 12 | 21 |
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Category by category
Coding GPT-5 Pro leads
GPT-5 Pro: 43.4 (#77), Qwen1.5-32B: 31.1 (#278)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| WeirdML | 60.4% | — |
| BigCodeBench Instruct | — | 32.3% |
| LMArena Coding | — | 1155 |
| BigCodeBench Complete | — | 42% |
| AlgoTune | 1.31 | — |
Reasoning GPT-5 Pro leads
GPT-5 Pro: 39.2 (#52), Qwen1.5-32B: 20.9 (#210)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| ARC-AGI-2 | 18.3% | — |
| SimpleBench | 61.6% | — |
| Kagi LLM Benchmark | 76.8% | — |
| ARC-AGI-1 | 70.2% | — |
| EnigmaEval | 18.8% | — |
| LMArena Hard Prompts | — | 1131 |
| Epoch Capabilities Index | 150.26 | — |
Math GPT-5 Pro leads
GPT-5 Pro: 48.0 (#53), Qwen1.5-32B: 30.5 (#207)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 19.5% | — |
| LMArena Math | — | 1155 |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge GPT-5 Pro leads
GPT-5 Pro: 56.2 (#39), Qwen1.5-32B: 13.5 (#291)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| GPQA Diamond | — | 30.7% |
| Humanity's Last Exam | 31.6% | — |
| LMArena Expert | — | 1126 |
| MMLU | — | 74.4% |
Multilingual Not comparable
GPT-5 Pro: —, Qwen1.5-32B: 31.6 (#254)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| LMArena Non-English | — | 1106 |
| LMArena Chinese | — | 1176 |
| LMArena French | — | 1100 |
| LMArena German | — | 1058 |
| LMArena Japanese | — | 1027 |
| LMArena Korean | — | 1007 |
| LMArena Russian | — | 1073 |
| LMArena Spanish | — | 1089 |
Instruction Following Not comparable
GPT-5 Pro: —, Qwen1.5-32B: 58.0 (#260)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| LMArena Instruction Following | — | 1116 |
Long Context Not comparable
GPT-5 Pro: —, Qwen1.5-32B: 34.7 (#241)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| LMArena Longer Query | — | 1146 |
Writing & Preference Not comparable
GPT-5 Pro: —, Qwen1.5-32B: 34.4 (#266)
| Benchmark | GPT-5 Pro | Qwen1.5-32B |
|---|---|---|
| LMArena Text | — | 1137 |
| LMArena Creative Writing | — | 1083 |
| LMArena Multi-Turn | — | 1140 |
Frequently asked questions
Is GPT-5 Pro better than Qwen1.5-32B?
GPT-5 Pro is the stronger model overall, scoring 46.2 to 30.0 on the Noometry Index.
Is GPT-5 Pro or Qwen1.5-32B better for coding?
GPT-5 Pro scores higher on coding benchmarks: 43.4 versus 31.1 in the Noometry coding category.
How many benchmarks do GPT-5 Pro and Qwen1.5-32B share?
0 benchmarks have published results for both models. GPT-5 Pro has 12 scored results on Noometry and Qwen1.5-32B has 21.