Model comparison
Claude Opus 4.7 vs Qwen3.6-27B
Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 #12 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 and Qwen3.6-27B share 13 comparable benchmark results. 1 of 8 categories are comparable. 8 results are unique to Claude Opus 4.7; 41 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 13
- Claude Opus 4.7 only
- 8
- Qwen3.6-27B only
- 41
- Comparable categories
- 1 / 8
Pick Claude Opus 4.7 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 13 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
Claude Opus 4.7 is clearly ahead on the BenchAlign aggregate, 71.94 to 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.7 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while Claude Opus 4.7 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. Claude Opus 4.7 gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.
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 Opus 4.7 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | Claude Opus 4.738.6 | Margin→ 50.6 | Qwen3.6-27B89.2 |
| Agentic | Claude Opus 4.7Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | Claude Opus 4.7Not measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Knowledge | Claude Opus 4.7Not measured | MarginNo overlap | Qwen3.6-27B53.3 |
| Multimodal | Claude Opus 4.7Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7$5 input / $25 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7Not available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7Not available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.71M | Qwen3.6-27B262K | Claude Opus 4.7 lists the larger context window. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | Claude Opus 4.7 | Qwen3.6-27B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 74% | 94.2% | Qwen3.6-27B leads |
| Gert LabsSource | 65.59% | 54.84% | Claude Opus 4.7 leads |
| ResearchClawBenchSource | 20.7% | — | Not comparable |
| OSWorld 2.0Source | 13.9% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| AA Agentic IndexSource | — | 27.0% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
Coding11 benchmarks
| Benchmark | Claude Opus 4.7 | Qwen3.6-27B | Result |
|---|---|---|---|
| Vibe Code BenchSource | 71.00% | — | Not comparable |
| React Native EvalsSource | 82.8% | — | Not comparable |
| AA-SciCodeSource | 50.1% | 39.8% | Claude Opus 4.7 leads |
| FrontierCode 1.1 MainSource | 38.5% | — | Not comparable |
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
| AA Coding IndexSource | — | 53.7% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | Claude Opus 4.7 | Qwen3.6-27B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.7% | 37.0% | Claude Opus 4.7 leads |
| AA-GPQA DiamondSource | 88.5% | 84.2% | Claude Opus 4.7 leads |
| AA-HLESource | 31.2% | 21.6% | Claude Opus 4.7 leads |
| AA-Omniscience IndexSource | 14.2% | -19.8% | Claude Opus 4.7 leads |
| AA-Omniscience AccuracySource | 43.5% | 19.2% | Claude Opus 4.7 leads |
| AA-Omniscience Hallucination RateSource | 51.9% | 48.3% | Qwen3.6-27B leads |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
MathQwen3.6-27B wins7 benchmarks
| Benchmark | Claude Opus 4.7 | Qwen3.6-27B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 43.793% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 22.917% | — | Not comparable |
| HMMT Feb 2025Source | — | 93.8% | Not comparable |
| HMMT Nov 2025Source | — | 90.7% | Not comparable |
| HMMT Feb 2026Source | — | 84.3% | Not comparable |
| MMAnswerBenchSource | — | 80.8% | Not comparable |
| AIME26Source | — | 94.1% | Not comparable |
Multimodal17 benchmarks
| Benchmark | Claude Opus 4.7 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 76.4% | 74.6% | Claude Opus 4.7 leads |
| Design Arena WebsiteSource | 1325 | — | Not comparable |
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.6% | 67.6% | Qwen3.6-27B leads |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 or Qwen3.6-27B?
Claude Opus 4.7 is ahead on BenchLM's BenchAlign leaderboard, 71.94 to 53.82.
Which is better for math, Claude Opus 4.7 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 38.6. Claude Opus 4.7 stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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