Model comparison
GPT-5.3 Chat vs Qwen1.5-32B
GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 30.0 on the Noometry Index.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. GPT-5.3 Chat scores higher in 8 categories and Qwen1.5-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.3 to 34.4.
- Qwen1.5-32B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Chat | Qwen1.5-32B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.1 | 30.0 |
| Released | 2026-03-03 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 128K | — |
| Max output | 16K | — |
| Input $ / M tokens | $1.75 | — |
| Output $ / M tokens | $14 | — |
| Results tracked | 18 | 21 |
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Category by category
Coding GPT-5.3 Chat leads
GPT-5.3 Chat: 40.8 (#124), Qwen1.5-32B: 31.1 (#278)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Coding | 1408 | 1155 |
| BigCodeBench Instruct | — | 32.3% |
| BigCodeBench Complete | — | 42% |
Reasoning GPT-5.3 Chat leads
GPT-5.3 Chat: 27.3 (#105), Qwen1.5-32B: 20.9 (#210)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1131 |
Math GPT-5.3 Chat leads
GPT-5.3 Chat: 35.4 (#146), Qwen1.5-32B: 30.5 (#207)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Math | 1389 | 1155 |
Knowledge GPT-5.3 Chat leads
GPT-5.3 Chat: 38.2 (#137), Qwen1.5-32B: 13.5 (#291)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Expert | 1397 | 1126 |
| GPQA Diamond | — | 30.7% |
| MMLU | — | 74.4% |
Multilingual GPT-5.3 Chat leads
GPT-5.3 Chat: 50.5 (#119), Qwen1.5-32B: 31.6 (#254)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Non-English | 1383 | 1106 |
| LMArena Chinese | 1433 | 1176 |
| LMArena French | 1398 | 1100 |
| LMArena German | 1384 | 1058 |
| LMArena Japanese | 1351 | 1027 |
| LMArena Korean | 1347 | 1007 |
| LMArena Russian | 1400 | 1073 |
| LMArena Spanish | 1371 | 1089 |
Instruction Following GPT-5.3 Chat leads
GPT-5.3 Chat: 73.0 (#124), Qwen1.5-32B: 58.0 (#260)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Instruction Following | 1378 | 1116 |
Long Context GPT-5.3 Chat leads
GPT-5.3 Chat: 42.6 (#115), Qwen1.5-32B: 34.7 (#241)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Longer Query | 1396 | 1146 |
Writing & Preference GPT-5.3 Chat leads
GPT-5.3 Chat: 63.3 (#65), Qwen1.5-32B: 34.4 (#266)
| Benchmark | GPT-5.3 Chat | Qwen1.5-32B |
|---|---|---|
| LMArena Text | 1389 | 1137 |
| LMArena Creative Writing | 1356 | 1083 |
| LMArena Multi-Turn | 1413 | 1140 |
| EQ-Bench Creative Writing | 1690 | — |
Frequently asked questions
Is GPT-5.3 Chat better than Qwen1.5-32B?
GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 30.0 on the Noometry Index.
Is GPT-5.3 Chat or Qwen1.5-32B better for coding?
GPT-5.3 Chat scores higher on coding benchmarks: 40.8 versus 31.1 in the Noometry coding category.
How many benchmarks do GPT-5.3 Chat and Qwen1.5-32B share?
17 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Qwen1.5-32B has 21.