Model comparison
Claude 4 Sonnet vs Qwen3.6-35B-A3B
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Claude 4 Sonnet unranked; Qwen3.6-35B-A3B #31
BenchAlign evidence: Claude 4 Sonnet supported; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude 4 Sonnet and Qwen3.6-35B-A3B share 15 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to Claude 4 Sonnet; 43 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 15
- Claude 4 Sonnet only
- 2
- Qwen3.6-35B-A3B only
- 43
- Comparable categories
- 1 / 8
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Claude 4 Sonnet only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6-35B-A3B is clearly ahead on the provisional aggregate, 59 to 48. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-35B-A3B's sharpest advantage is in coding, where it averages 73.8 against 72.7. The single biggest benchmark swing on the page is SWE-bench Verified, 72.7% to 73.4%.
Qwen3.6-35B-A3B is the reasoning model in the pair, while Claude 4 Sonnet is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 200K for Claude 4 Sonnet.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude 4 Sonnet | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Coding | Claude 4 Sonnet72.7 | Margin→ 1.1 | Qwen3.6-35B-A3B73.8 |
| Agentic | Claude 4 SonnetNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Knowledge | Claude 4 SonnetNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.8 |
| Math | Claude 4 SonnetNot measured | MarginNo overlap | Qwen3.6-35B-A3B88.2 |
| Multimodal | Claude 4 SonnetNot measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 72.7%B 73.4%Winner: Qwen3.6-35B-A3BΔ 0.7SWE-bench Verified: Claude 4 Sonnet scored 72.7%; Qwen3.6-35B-A3B scored 73.4%. Qwen3.6-35B-A3B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 4 Sonnet | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 4 Sonnet$3 input / $15 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude 4 Sonnet40 tok/s | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude 4 Sonnet1.33 s | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude 4 Sonnet200K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | Claude 4 Sonnet | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 52.3% | 95.3% | Qwen3.6-35B-A3B leads |
| Gert LabsSource | 39.66% | 42.65% | Qwen3.6-35B-A3B leads |
| JobBenchSource | 18.4% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| Claw-EvalSource | — | 68.7% | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| τ³-bench resultsSource | — | 67.2% | Not comparable |
| VITA-BenchSource | — | 35.6% | Not comparable |
| DeepPlanningSource | — | 25.9% | Not comparable |
| ToolathlonSource | — | 26.9% | Not comparable |
| MCP AtlasSource | — | 62.8% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
| AA Agentic IndexSource | — | 21.4% | Not comparable |
| GDPval-AASource | — | 27.4% | Not comparable |
| GDPval-AASource | — | 1049 | Not comparable |
CodingQwen3.6-35B-A3B wins9 benchmarks
| Benchmark | Claude 4 Sonnet | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 72.7% | 73.4% | Qwen3.6-35B-A3B leads |
| Terminal-Bench HardSource | 27.3% | 34.8% | Qwen3.6-35B-A3B leads |
| AA-SciCodeSource | 37.3% | 35.8% | Claude 4 Sonnet leads |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| SWE-bench ProSource | — | 49.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| LiveCodeBenchSource | — | 80.4% | Not comparable |
| NL2RepoSource | — | 29.4% | Not comparable |
| AA Coding IndexSource | — | 41.9% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Claude 4 Sonnet | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.5% | 31.6% | Qwen3.6-35B-A3B leads |
| AA-GPQA DiamondSource | 68.3% | 84.1% | Qwen3.6-35B-A3B leads |
| AA-HLESource | 4.0% | 20.2% | Qwen3.6-35B-A3B leads |
| AA-Omniscience IndexSource | -9.2% | -21.4% | Claude 4 Sonnet leads |
| AA-Omniscience AccuracySource | 22.4% | 18.9% | Claude 4 Sonnet leads |
| AA-Omniscience Hallucination RateSource | 40.8% | 49.7% | Claude 4 Sonnet leads |
| MMLU-ProSource | — | 85.2% | Not comparable |
| SuperGPQASource | — | 64.7% | Not comparable |
| C-EvalSource | — | 90% | Not comparable |
| GPQASource | — | 86% | Not comparable |
| HLESource | — | 21.4% | Not comparable |
Math5 benchmarks
Multimodal16 benchmarks
| Benchmark | Claude 4 Sonnet | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 62.4% | 75.0% | Qwen3.6-35B-A3B leads |
| Design Arena WebsiteSource | 1180 | — | Not comparable |
| MMMUSource | — | 81.7% | Not comparable |
| MMMU-ProSource | — | 75.3% | Not comparable |
| RealWorldQASource | — | 85.3% | Not comparable |
| OmniDocBench 1.5Source | — | 89.9% | Not comparable |
| CharXivSource | — | 78% | Not comparable |
| SimpleVQASource | — | 58.9% | Not comparable |
| CC-OCRSource | — | 81.9% | Not comparable |
| AI2D_TESTSource | — | 92.7% | Not comparable |
| RefCOCO (avg)Source | — | 92.0% | Not comparable |
| ODINW13Source | — | 50.8% | Not comparable |
| Video-MME (with subtitle)Source | — | 86.6% | Not comparable |
| Video-MME (w/o subtitle)Source | — | 82.5% | Not comparable |
| VideoMMMUSource | — | 83.7% | Not comparable |
| MLVU (M-Avg)Source | — | 86.2% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude 4 Sonnet | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 45.4% | 64.4% | Qwen3.6-35B-A3B leads |
Frequently Asked Questions (2)
Which is better, Claude 4 Sonnet or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 59 to 48. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 72.7% and 73.4%.
Which is better for coding, Claude 4 Sonnet or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for coding in this comparison, averaging 73.8 versus 72.7. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
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