Model comparison
Claude Opus 4.5 vs Qwen3.6-27B
Head-to-head evidence from 35 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.5 #34 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.5 and Qwen3.6-27B share 35 comparable benchmark results. 5 of 8 categories are comparable. 24 results are unique to Claude Opus 4.5; 19 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 35
- Claude Opus 4.5 only
- 24
- Qwen3.6-27B only
- 19
- Comparable categories
- 5 / 8
Pick Claude Opus 4.5 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 35 shared benchmark results across 7 evidence categories; 5 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 4.5 is clearly ahead on the BenchAlign aggregate, 64.22 to 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.5's sharpest advantage is in knowledge, where it averages 58.1 against 53.3. The single biggest benchmark swing on the page is CharXiv, 68.5% to 78.4%. Qwen3.6-27B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Claude Opus 4.5 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 4.5 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. Qwen3.6-27B gives you the larger context window at 262K, compared with 200K for Claude Opus 4.5.
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 4.5 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | Claude Opus 4.557.5 | Margin→ 31.7 | Qwen3.6-27B89.2 |
| Multimodal | Claude Opus 4.569.9 | Margin→ 6.8 | Qwen3.6-27B76.7 |
| Coding | Claude Opus 4.571.7 | Margin→ 5.8 | Qwen3.6-27B77.5 |
| Knowledge | Claude Opus 4.558.1 | Margin← 4.8 | Qwen3.6-27B53.3 |
| Agentic | Claude Opus 4.562.6 | Margin← 3.3 | Qwen3.6-27B59.3 |
| Reasoning | Claude Opus 4.564.4 | MarginNo overlap | Qwen3.6-27BNot measured |
| Multilingual | Claude Opus 4.585.7 | MarginNo overlap | Qwen3.6-27BNot measured |
| Inst. Following | Claude Opus 4.569.5 | MarginNo overlap | Qwen3.6-27BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
CharXiv
MultimodalA 68.5%B 78.4%Winner: Qwen3.6-27BΔ 9.9CharXiv: Claude Opus 4.5 scored 68.5%; Qwen3.6-27B scored 78.4%. Qwen3.6-27B wins this benchmark. - Source ↗
HLE
KnowledgeA 30.8%B 24%Winner: Claude Opus 4.5Δ 6.8HLE: Claude Opus 4.5 scored 30.8%; Qwen3.6-27B scored 24%. Claude Opus 4.5 wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 70.6%B 75.8%Winner: Qwen3.6-27BΔ 5.2MMMU-Pro: Claude Opus 4.5 scored 70.6%; Qwen3.6-27B scored 75.8%. Qwen3.6-27B wins this benchmark. - Source ↗
SuperGPQA
KnowledgeA 70.6%B 66%Winner: Claude Opus 4.5Δ 4.6SuperGPQA: Claude Opus 4.5 scored 70.6%; Qwen3.6-27B scored 66%. Claude Opus 4.5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 80.9%B 77.2%Winner: Claude Opus 4.5Δ 3.7SWE-bench Verified: Claude Opus 4.5 scored 80.9%; Qwen3.6-27B scored 77.2%. Claude Opus 4.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.5 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.5$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 4.546 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.51.01 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.5200K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
AgenticClaude Opus 4.5 wins21 benchmarks
| Benchmark | Claude Opus 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.3% | 59.3% | Tie |
| OSWorld-VerifiedSource | 66.3% | — | Not comparable |
| OSWorldSource | 66.3% | — | Not comparable |
| Claw-EvalSource | 59.6% | 72.4% | Qwen3.6-27B leads |
| QwenClawBenchSource | 52.3% | 53.4% | Qwen3.6-27B leads |
| τ³-bench resultsSource | 70.2% | — | Not comparable |
| VITA-BenchSource | 23.3% | — | Not comparable |
| DeepPlanningSource | 26.4% | — | Not comparable |
| ToolathlonSource | 43.5% | — | Not comparable |
| MCP AtlasSource | 42.3% | — | Not comparable |
| MCP-TasksSource | 71.8% | — | Not comparable |
| WideResearchSource | 76.4% | — | Not comparable |
| CyberGymSource | 50.6% | — | Not comparable |
| τ²-bench resultsSource | 86.3% | 94.2% | Qwen3.6-27B leads |
| Gert LabsSource | 64.23% | 54.84% | Claude Opus 4.5 leads |
| JobBenchSource | 32.3% | — | 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 |
CodingQwen3.6-27B wins9 benchmarks
| Benchmark | Claude Opus 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.9% | 77.2% | Claude Opus 4.5 leads |
| LiveCodeBench v6Source | 84.8% | — | Not comparable |
| SWE-bench ProSource | 57.1% | 53.5% | Claude Opus 4.5 leads |
| SWE MultilingualSource | 77.5% | 71.3% | Claude Opus 4.5 leads |
| NL2RepoSource | 43.2% | 36.2% | Claude Opus 4.5 leads |
| AA-SciCodeSource | 47.0% | 39.8% | Claude Opus 4.5 leads |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| AA Coding IndexSource | — | 53.7% | Not comparable |
Reasoning4 benchmarks
KnowledgeClaude Opus 4.5 wins13 benchmarks
| Benchmark | Claude Opus 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| GPQASource | 87% | 87.8% | Qwen3.6-27B leads |
| SuperGPQASource | 70.6% | 66% | Claude Opus 4.5 leads |
| MMLU-ProSource | 89.5% | 86.2% | Claude Opus 4.5 leads |
| MMLU-ReduxSource | 96.6% | 93.5% | Claude Opus 4.5 leads |
| C-EvalSource | 92.2% | 91.4% | Claude Opus 4.5 leads |
| HLESource | 30.8% | 24% | Claude Opus 4.5 leads |
| Artificial Analysis Intelligence IndexSource | 34.7% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 81.0% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 12.9% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -3.9% | -19.8% | Claude Opus 4.5 leads |
| AA-Omniscience AccuracySource | 40.7% | 19.2% | Claude Opus 4.5 leads |
| AA-Omniscience Hallucination RateSource | 75.4% | 48.3% | Qwen3.6-27B leads |
| AA MMLU-ProSource | 88.9% | — | Not comparable |
MathQwen3.6-27B wins7 benchmarks
| Benchmark | Claude Opus 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| AIME26Source | 95.1% | 94.1% | Claude Opus 4.5 leads |
| HMMT Feb 2025Source | 92.9% | 93.8% | Qwen3.6-27B leads |
| HMMT Nov 2025Source | 93.3% | 90.7% | Claude Opus 4.5 leads |
| HMMT Feb 2026Source | 85.3% | 84.3% | Claude Opus 4.5 leads |
| MMAnswerBenchSource | 84.0% | 80.8% | Claude Opus 4.5 leads |
| FrontierMath v2 (Tiers 1-3)Source | 20.690% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 4.167% | — | Not comparable |
Multilingual2 benchmarks
MultimodalQwen3.6-27B wins19 benchmarks
| Benchmark | Claude Opus 4.5 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMU-ProSource | 70.6% | 75.8% | Qwen3.6-27B leads |
| MathVisionSource | 74.3% | — | Not comparable |
| CharXivSource | 68.5% | 78.4% | Qwen3.6-27B leads |
| VideoMMMUSource | 84.4% | 84.4% | Tie |
| ScreenSpot ProSource | 45.7% | — | Not comparable |
| V*Source | 67.0% | 94.7% | Qwen3.6-27B leads |
| AA-MMMU-ProSource | 71.2% | 74.6% | Qwen3.6-27B leads |
| Design Arena WebsiteSource | 1277 | — | Not comparable |
| MMMUSource | — | 82.9% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | 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 |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
Frequently Asked Questions (6)
Which is better, Claude Opus 4.5 or Qwen3.6-27B?
Claude Opus 4.5 is ahead on BenchLM's BenchAlign leaderboard, 64.22 to 53.82. The biggest single separator in this matchup is CharXiv, where the scores are 68.5% and 78.4%.
Which is better for knowledge tasks, Claude Opus 4.5 or Qwen3.6-27B?
Claude Opus 4.5 has the edge for knowledge tasks in this comparison, averaging 58.1 versus 53.3. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Opus 4.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 71.7. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, Claude Opus 4.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 57.5. Inside this category, MMAnswerBench is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Claude Opus 4.5 or Qwen3.6-27B?
Claude Opus 4.5 has the edge for agentic tasks in this comparison, averaging 62.6 versus 59.3. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Claude Opus 4.5 or Qwen3.6-27B?
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 76.7 versus 69.9. Inside this category, V* is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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