Model comparison
Claude Sonnet 4.6 vs Qwen2.5 32B Instruct
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 30.1 on the Noometry Index. Qwen2.5 32B Instruct costs 4.9× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 4 categories and Qwen2.5 32B Instruct in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Sonnet 4.6 leads 52.9 to 16.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 85.8% for Claude Sonnet 4.6 and 7.4% for Qwen2.5 32B Instruct.
- Qwen2.5 32B Instruct is cheaper at $0.70 / $2.80 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.6.
- Claude Sonnet 4.6 accepts more context: 1M tokens versus 131K.
- Qwen2.5 32B Instruct has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4.6 | Qwen2.5 32B Instruct | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 50.3 | 30.1 |
| Released | 2026-02-17 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $3 | $0.70 |
| Output $ / M tokens | $15 | $2.80 |
| Results tracked | 57 | 7 |
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Category by category
Coding Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.3 (#67), Qwen2.5 32B Instruct: 38.7 (#169)
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| LMArena WebDev | 1522 | — |
| SciCode | 46.8% | — |
| WeirdML | 66.1% | — |
| BigCodeBench Instruct | — | 45% |
| LMArena Coding | 1504 | — |
| BigCodeBench Complete | — | 52.3% |
| ALE-Bench | 1,327 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4.6: 39.1 (#28), Qwen2.5 32B Instruct: —
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#45), Qwen2.5 32B Instruct: 19.2 (#266)
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| Chess Puzzles | 13% | 0% |
| Epoch Capabilities Index | 152.24 | 128.52 |
| ARC-AGI-2 | 60.4% | — |
| NYT Connections (extended) | 80.9% | — |
| ARC-AGI-1 | 86.5% | — |
| CritPt | 3.1% | — |
| Thematic Generalization | 76.3% | — |
| LMArena Hard Prompts | 1484 | — |
| Mystery Game Puzzles | 16% | — |
| DTBench | 89.9% | — |
| LMCA | 46.5% | — |
| ForecastBench | 62 | — |
Math Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 52.9 (#49), Qwen2.5 32B Instruct: 16.2 (#296)
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 85.8% | 7.4% |
| ProofBench | 45% | — |
| LMArena Math | 1462 | — |
| MATH Level 5 | — | 56.1% |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |
Knowledge Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 51.7 (#65), Qwen2.5 32B Instruct: 24.9 (#266)
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 87.4% | 46.1% |
| SimpleQA Verified | 35.5% | — |
| Vectara Hallucination Rate | 10.6% | — |
| LMArena Expert | 1500 | — |
Multimodal Not comparable
Claude Sonnet 4.6: 38.0 (#68), Qwen2.5 32B Instruct: —
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual Not comparable
Claude Sonnet 4.6: 54.4 (#41), Qwen2.5 32B Instruct: —
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1440 | — |
| LMArena Chinese | 1491 | — |
| LMArena French | 1465 | — |
| LMArena German | 1428 | — |
| LMArena Japanese | 1420 | — |
| LMArena Korean | 1411 | — |
| LMArena Russian | 1440 | — |
| LMArena Spanish | 1464 | — |
Instruction Following Not comparable
Claude Sonnet 4.6: 77.4 (#25), Qwen2.5 32B Instruct: —
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Instruction Following | 1475 | — |
Long Context Not comparable
Claude Sonnet 4.6: 45.3 (#44), Qwen2.5 32B Instruct: —
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Longer Query | 1479 | — |
Writing & Preference Not comparable
Claude Sonnet 4.6: 70.2 (#22), Qwen2.5 32B Instruct: —
| Benchmark | Claude Sonnet 4.6 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1458 | — |
| LMArena Creative Writing | 1435 | — |
| EQ-Bench Creative Writing | 1810 | — |
| EQ-Bench 4 | 1207 | — |
| LMArena Multi-Turn | 1464 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than Qwen2.5 32B Instruct?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 30.1 on the Noometry Index. Qwen2.5 32B Instruct costs 4.9× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 4.6 or Qwen2.5 32B Instruct?
Qwen2.5 32B Instruct is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Claude Sonnet 4.6 lists at $3 and $15.
Is Claude Sonnet 4.6 or Qwen2.5 32B Instruct better for coding?
Claude Sonnet 4.6 scores higher on coding benchmarks: 46.3 versus 38.7 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 4.6 does, with 1M tokens against 131K.
How many benchmarks do Claude Sonnet 4.6 and Qwen2.5 32B Instruct share?
4 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and Qwen2.5 32B Instruct has 7.