Model comparison
Claude 3.7 Sonnet vs Qwen2.5-Coder-32B
Claude 3.7 Sonnet is the stronger model overall, scoring 39.4 to 32.9 on the Noometry Index.
Last verified . 22 shared benchmarks.
Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. Claude 3.7 Sonnet scores higher in 7 categories and Qwen2.5-Coder-32B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude 3.7 Sonnet leads 41.1 to 22.4.
- The biggest single-benchmark swing is Aider Polyglot: 64.9% for Claude 3.7 Sonnet and 16.4% for Qwen2.5-Coder-32B.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.
Side by side
| Claude 3.7 Sonnet | Qwen2.5-Coder-32B | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 39.4 | 32.9 |
| Released | 2025-02-24 | 2024-09-18 |
| Weights | Proprietary | Open |
| Context window | — | 33K |
| Max output | — | 29K |
| Input $ / M tokens | — | $0.66 |
| Output $ / M tokens | — | $1 |
| Results tracked | 58 | 31 |
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Category by category
Coding Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 41.1 (#120), Qwen2.5-Coder-32B: 22.4 (#328)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| SWE-bench Verified (bash only) | 52.8% | 9% |
| Aider Polyglot | 64.9% | 16.4% |
| LiveBench Coding | 74.5% | 56.9% |
| LMArena Coding | 1361 | 1276 |
| SWE-bench Verified | 61% | — |
| GSO | 3.8% | — |
| BigCodeBench Instruct | — | 49% |
| BigCodeBench Complete | — | 58% |
| CadEval | 54% | — |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |
Agentic & Tool Use Not comparable
Claude 3.7 Sonnet: 33.9 (#46), Qwen2.5-Coder-32B: —
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| TheAgentCompany | 30.9% | — |
| Cybench | 20% | — |
| DeepResearch Bench | 43.6% | — |
| OSWorld | 35.8% | — |
| METR Time Horizons | 60% | — |
Reasoning Qwen2.5-Coder-32B leads
Claude 3.7 Sonnet: 18.7 (#252), Qwen2.5-Coder-32B: 20.4 (#220)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Reasoning | 87.8% | 42.1% |
| LMArena Hard Prompts | 1333 | 1251 |
| LiveBench Data Analysis | 74% | 49.9% |
| Epoch Capabilities Index | 141.16 | 119.41 |
| LiveBench | 76.1% | 46.2% |
| ARC-AGI-2 | 0.9% | — |
| SimpleBench | 46.4% | — |
| ARC-AGI-1 | 28.6% | — |
| EnigmaEval | 4.2% | — |
| ForecastBench | 61.8 | — |
| HellaSwag | — | 83% |
| WinoGrande | — | 80.8% |
Math Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 35.7 (#137), Qwen2.5-Coder-32B: 30.8 (#203)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Math | 79% | 46.6% |
| LMArena Math | 1336 | 1251 |
| OTIS Mock AIME 2024-2025 | 57.8% | — |
| Omni-MATH | 33% | — |
| MATH Level 5 | 91.2% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
| GSM8K | — | 93% |
Knowledge Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 39.7 (#117), Qwen2.5-Coder-32B: 32.9 (#200)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1321 | 1221 |
| GPQA Diamond | 79.7% | — |
| Humanity's Last Exam | 8% | — |
| MMLU-Pro | 78.4% | — |
| Confabulations | 14.7% | — |
| GPQA (HELM) | 60.8% | — |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |
Multimodal Not comparable
Claude 3.7 Sonnet: 33.1 (#90), Qwen2.5-Coder-32B: —
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1169 | — |
| GeoBench | 68% | — |
| VPCT | 39% | — |
| SpatialViz-Bench | 33.9% | — |
Multilingual Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 44.3 (#174), Qwen2.5-Coder-32B: 38.0 (#230)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1296 | 1205 |
| LMArena Chinese | 1299 | 1222 |
| LMArena Russian | 1311 | 1228 |
| LMArena French | 1302 | — |
| LMArena German | 1301 | — |
| LMArena Japanese | 1268 | — |
| LMArena Korean | 1249 | — |
| LMArena Spanish | 1299 | — |
Instruction Following Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 73.1 (#120), Qwen2.5-Coder-32B: 61.6 (#240)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Instruction Following | 81.3% | 58.7% |
| LMArena Instruction Following | 1352 | 1223 |
| IFEval | 83.4% | — |
Long Context Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 50.2 (#10), Qwen2.5-Coder-32B: 37.9 (#204)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1373 | 1251 |
| Fiction.LiveBench | 83.3% | — |
Writing & Preference Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 54.6 (#145), Qwen2.5-Coder-32B: 41.8 (#235)
| Benchmark | Claude 3.7 Sonnet | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1314 | 1230 |
| LMArena Creative Writing | 1332 | 1174 |
| LMArena Multi-Turn | 1339 | 1222 |
| LiveBench Language | 59.9% | 23.3% |
| Short-Story Creative Writing | 81.1% | — |
| EQ-Bench Creative Writing | 1412 | — |
| WildBench | 81.4% | — |
Frequently asked questions
Is Claude 3.7 Sonnet better than Qwen2.5-Coder-32B?
Claude 3.7 Sonnet is the stronger model overall, scoring 39.4 to 32.9 on the Noometry Index.
Is Claude 3.7 Sonnet or Qwen2.5-Coder-32B better for coding?
Claude 3.7 Sonnet scores higher on coding benchmarks: 41.1 versus 22.4 in the Noometry coding category.
How many benchmarks do Claude 3.7 Sonnet and Qwen2.5-Coder-32B share?
22 benchmarks have published results for both models. Claude 3.7 Sonnet has 58 scored results on Noometry and Qwen2.5-Coder-32B has 31.