Model comparison
GPT-4.5 vs Qwen1.5-32B
GPT-4.5 is the stronger model overall, scoring 37.2 to 30.5 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GPT-4.5 scores higher in 6 categories and Qwen1.5-32B in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-4.5 leads 56.9 to 34.2.
- The biggest single-benchmark swing is GPQA Diamond: 68.7% for GPT-4.5 and 30.7% for Qwen1.5-32B.
- Qwen1.5-32B has downloadable open weights; the other is API-only.
Side by side
| GPT-4.5 | Qwen1.5-32B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 37.2 | 30.5 |
| Released | 2025-02-27 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 42 | 21 |
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Category by category
Coding GPT-4.5 leads
GPT-4.5: 42.2 (#109), Qwen1.5-32B: 31.7 (#282)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Coding | 1396 | 1155 |
| Aider Polyglot | 44.9% | — |
| WeirdML | 39.4% | — |
| BigCodeBench Instruct | — | 32.3% |
| LiveBench Coding | 75.2% | — |
| BigCodeBench Complete | — | 42% |
Agentic & Tool Use Not comparable
GPT-4.5: 27.9 (#97), Qwen1.5-32B: —
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| Cybench | 17.5% | — |
Reasoning Qwen1.5-32B leads
GPT-4.5: 13.9 (#330), Qwen1.5-32B: 21.8 (#212)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Hard Prompts | 1403 | 1130 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 34.5% | — |
| ARC-AGI-1 | 10.3% | — |
| EnigmaEval | 3.2% | — |
| LiveBench Reasoning | 71.1% | — |
| LiveBench Data Analysis | 64.3% | — |
| Epoch Capabilities Index | 136.74 | — |
| ForecastBench | 61.7 | — |
| LiveBench | 69% | — |
Math Too close to call
GPT-4.5: 32.6 (#211), Qwen1.5-32B: 33.0 (#207)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Math | 1412 | 1155 |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| LiveBench Math | 69.3% | — |
| MATH Level 5 | 78.6% | — |
Knowledge GPT-4.5 leads
GPT-4.5: 32.5 (#211), Qwen1.5-32B: 13.5 (#296)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| GPQA Diamond | 68.7% | 30.7% |
| LMArena Expert | 1394 | 1126 |
| Humanity's Last Exam | 5.4% | — |
| Confabulations | 13.6% | — |
| MMLU | — | 74.4% |
Multimodal Not comparable
GPT-4.5: 37.6 (#71), Qwen1.5-32B: —
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Vision | 1195 | — |
| VPCT | 45% | — |
Multilingual GPT-4.5 leads
GPT-4.5: 52.5 (#83), Qwen1.5-32B: 31.4 (#259)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Non-English | 1413 | 1106 |
| LMArena Chinese | 1421 | 1177 |
| LMArena French | 1418 | 1101 |
| LMArena German | 1457 | 1058 |
| LMArena Japanese | 1416 | 1027 |
| LMArena Korean | 1392 | 1008 |
| LMArena Russian | 1419 | 1073 |
| LMArena Spanish | — | 1089 |
Instruction Following GPT-4.5 leads
GPT-4.5: 72.6 (#134), Qwen1.5-32B: 57.7 (#265)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1116 |
| LiveBench Instruction Following | 72.3% | — |
Long Context GPT-4.5 leads
GPT-4.5: 40.4 (#155), Qwen1.5-32B: 34.7 (#246)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Longer Query | 1406 | 1146 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference GPT-4.5 leads
GPT-4.5: 56.9 (#134), Qwen1.5-32B: 34.2 (#271)
| Benchmark | GPT-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Text | 1417 | 1137 |
| LMArena Creative Writing | 1394 | 1083 |
| LMArena Multi-Turn | 1444 | 1140 |
| Short-Story Creative Writing | 75.6% | — |
| EQ-Bench Creative Writing | 1258 | — |
| LiveBench Language | 61.5% | — |
Frequently asked questions
Is GPT-4.5 better than Qwen1.5-32B?
GPT-4.5 is the stronger model overall, scoring 37.2 to 30.5 on the Noometry Index.
Is GPT-4.5 or Qwen1.5-32B better for coding?
GPT-4.5 scores higher on coding benchmarks: 42.2 versus 31.7 in the Noometry coding category.
How many benchmarks do GPT-4.5 and Qwen1.5-32B share?
17 benchmarks have published results for both models. GPT-4.5 has 42 scored results on Noometry and Qwen1.5-32B has 21.