Model comparison
Claude 4.1 Opus vs Qwen3.6-35B-A3B
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Claude 4.1 Opus unranked; Qwen3.6-35B-A3B #31
BenchAlign evidence: Claude 4.1 Opus supported; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude 4.1 Opus and Qwen3.6-35B-A3B share 2 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to Claude 4.1 Opus; 56 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 2
- Claude 4.1 Opus only
- 2
- Qwen3.6-35B-A3B only
- 56
- Comparable categories
- 1 / 8
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 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 is the reasoning model in the pair, while Claude 4.1 Opus 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 4.1 Opus.
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 4.1 Opus | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Coding | Claude 4.1 Opus74.5 | Margin← 0.7 | Qwen3.6-35B-A3B73.8 |
| Agentic | Claude 4.1 OpusNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Knowledge | Claude 4.1 OpusNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.8 |
| Math | Claude 4.1 OpusNot measured | MarginNo overlap | Qwen3.6-35B-A3B88.2 |
| Multimodal | Claude 4.1 OpusNot 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 74.5%B 73.4%Winner: Claude 4.1 OpusΔ 1.1SWE-bench Verified: Claude 4.1 Opus scored 74.5%; Qwen3.6-35B-A3B scored 73.4%. Claude 4.1 Opus wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 4.1 Opus | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 4.1 Opus$15 input / $75 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude 4.1 Opus29 tok/s | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude 4.1 Opus1.66 s | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude 4.1 Opus200K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | Claude 4.1 Opus | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| JobBenchSource | 21.9% | — | 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 |
| τ²-bench resultsSource | — | 95.3% | Not comparable |
| GDPval-AASource | — | 27.4% | Not comparable |
| GDPval-AASource | — | 1049 | Not comparable |
| Gert LabsSource | — | 42.65% | Not comparable |
CodingClaude 4.1 Opus wins9 benchmarks
| Benchmark | Claude 4.1 Opus | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 74.5% | 73.4% | Claude 4.1 Opus 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 |
| Terminal-Bench HardSource | — | 34.8% | Not comparable |
| AA-SciCodeSource | — | 35.8% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Claude 4.1 Opus | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 28.2% | 31.6% | Qwen3.6-35B-A3B 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 |
| AA-GPQA DiamondSource | — | 84.1% | Not comparable |
| AA-HLESource | — | 20.2% | Not comparable |
| AA-Omniscience IndexSource | — | -21.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 18.9% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 49.7% | Not comparable |
Math5 benchmarks
Multimodal16 benchmarks
| Benchmark | Claude 4.1 Opus | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1211 | — | 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 |
| AA-MMMU-ProSource | — | 75.0% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude 4.1 Opus | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 64.4% | Not comparable |
Frequently Asked Questions (2)
Which is better, Claude 4.1 Opus 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 74.5% and 73.4%.
Which is better for coding, Claude 4.1 Opus or Qwen3.6-35B-A3B?
Claude 4.1 Opus has the edge for coding in this comparison, averaging 74.5 versus 73.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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