Model comparison
Claude Sonnet 4 vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 40.6 on the Noometry Index.
Last verified . 7 shared benchmarks.
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. Claude Sonnet 4 scores higher in 2 categories and Qwen3.6 27B in 3 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 41.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 71.1% for Claude Sonnet 4 and 91.1% for Qwen3.6 27B.
- Qwen3.6 27B is cheaper at $0.60 / $3.60 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.
- Qwen3.6 27B accepts more context: 262K tokens versus 200K.
- Qwen3.6 27B has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4 | Qwen3.6 27B | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 40.6 | 41.9 |
| Released | 2025-05-22 | 2026-04-22 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 64K | 66K |
| Input $ / M tokens | $3 | $0.60 |
| Output $ / M tokens | $15 | $3.60 |
| Results tracked | 58 | 11 |
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Category by category
Coding Claude Sonnet 4 leads
Claude Sonnet 4: 44.0 (#70), Qwen3.6 27B: 38.5 (#162)
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| SciCode | 40% | 37.3% |
| SWE-bench Verified (bash only) | 64.9% | — |
| Aider Polyglot | 61.3% | — |
| GSO | 4.9% | — |
| WeirdML | 46.1% | — |
| LMArena Coding | 1414 | — |
| ALE-Bench | 655.35 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4: 38.3 (#29), Qwen3.6 27B: —
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| TheAgentCompany | 33.1% | — |
| Cybench | 35% | — |
| DeepResearch Bench | 46.6% | — |
| OSWorld | 43.9% | — |
| METR Time Horizons | 62% | — |
Reasoning Qwen3.6 27B leads
Claude Sonnet 4: 23.0 (#169), Qwen3.6 27B: 24.4 (#148)
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| CritPt | 0.3% | 0.9% |
| DTBench | 77.1% | 78.1% |
| LMCA | 29% | 34.5% |
| Epoch Capabilities Index | 141.69 | 146.47 |
| ARC-AGI-2 | 5.9% | — |
| SimpleBench | 45.5% | — |
| Kagi LLM Benchmark | 73% | — |
| ARC-AGI-1 | 40% | — |
| Chess Puzzles | — | 22% |
| EnigmaEval | 3.1% | — |
| LMArena Hard Prompts | 1372 | — |
| Mystery Game Puzzles | — | 7% |
| ForecastBench | 60.2 | — |
Math Qwen3.6 27B leads
Claude Sonnet 4: 41.5 (#71), Qwen3.6 27B: 47.5 (#56)
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 71.1% | 91.1% |
| FrontierMath (Tiers 1-3) | — | 35.1% |
| Omni-MATH | 60.2% | — |
| LMArena Math | 1375 | — |
| MATH Level 5 | 84.4% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3.6 27B leads
Claude Sonnet 4: 41.6 (#99), Qwen3.6 27B: 52.4 (#58)
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | 79.2% | 85.9% |
| Humanity's Last Exam | 7.8% | — |
| MMLU-Pro | 84.3% | — |
| Confabulations | 13.2% | — |
| Vectara Hallucination Rate | 10.3% | — |
| GPQA (HELM) | 70.6% | — |
| LMArena Expert | 1371 | — |
Multimodal Not comparable
Claude Sonnet 4: 25.6 (#116), Qwen3.6 27B: —
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| LMArena Vision | 1191 | — |
| GeoBench | 37% | — |
| VPCT | 34% | — |
| MindCube | 44.8% | — |
Multilingual Not comparable
Claude Sonnet 4: 46.9 (#151), Qwen3.6 27B: —
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| LMArena Non-English | 1333 | — |
| LMArena Chinese | 1351 | — |
| LMArena French | 1364 | — |
| LMArena German | 1331 | — |
| LMArena Japanese | 1301 | — |
| LMArena Korean | 1293 | — |
| LMArena Russian | 1355 | — |
| LMArena Spanish | 1356 | — |
Instruction Following Not comparable
Claude Sonnet 4: 71.8 (#141), Qwen3.6 27B: —
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| IFEval | 84% | — |
| LMArena Instruction Following | 1375 | — |
Long Context Not comparable
Claude Sonnet 4: 33.6 (#254), Qwen3.6 27B: —
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| Fiction.LiveBench | 46.9% | — |
| LMArena Longer Query | 1398 | — |
Writing & Preference Claude Sonnet 4 leads
Claude Sonnet 4: 57.3 (#127), Qwen3.6 27B: 50.3 (#180)
| Benchmark | Claude Sonnet 4 | Qwen3.6 27B |
|---|---|---|
| LMArena Text | 1351 | — |
| LMArena Creative Writing | 1345 | — |
| Short-Story Creative Writing | 81.4% | — |
| EQ-Bench Creative Writing | 1483 | — |
| WildBench | 83.8% | — |
| EQ-Bench 4 | — | 1026 |
| LMArena Multi-Turn | 1376 | — |
Frequently asked questions
Is Claude Sonnet 4 better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 40.6 on the Noometry Index.
Which is cheaper, Claude Sonnet 4 or Qwen3.6 27B?
Qwen3.6 27B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; Claude Sonnet 4 lists at $3 and $15.
Is Claude Sonnet 4 or Qwen3.6 27B better for coding?
Claude Sonnet 4 scores higher on coding benchmarks: 44.0 versus 38.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 27B does, with 262K tokens against 200K.
How many benchmarks do Claude Sonnet 4 and Qwen3.6 27B share?
7 benchmarks have published results for both models. Claude Sonnet 4 has 58 scored results on Noometry and Qwen3.6 27B has 11.