LLM Comparison
Qwen3.5-27B vs Claude Opus 4.7
Side-by-side specs, pricing & capabilities · Updated May 2026
Price vs Intelligence
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 49 55.8 | 71 4.7 |
| Family | Qwen | Claude |
| Status | Current | Current |
| Release Date | Feb 2026 | Apr 2026 |
| Context Window | 262K tokens | 1.0M tokens |
| Input Price | $0.20/M tokens | $5.00/M tokens |
| Output Price | $1.56/M tokens | $25.00/M tokens |
| Pricing Notes | — | Cache read: $0.5000/M tokens |
| Capabilities | textvisionvideocode | textvisioncodetool-use |
| Max Output | 66K tokens | 128K tokens |
| API Identifier | qwen/qwen3.5-27b | anthropic/claude-opus-4.7 |
| Benchmarks | ||
| MMLU-Pro | 86.1alibaba | 78.1anthropic |
| GPQA Diamond | 85.5alibaba | 94.2anthropic |
| SWE-bench Verified | 72.4alibaba | 87.6anthropic |
| MathVision | 86alibaba | — |
| TAU2-Bench | 79alibaba | — |
| IFEval | 91.5alibaba | — |
| MMLU | — | 84.7anthropic |
| MMMLU | — | 92anthropic |
| HLE | — | 54.7artificial-analysis |
| SWE-bench Pro | — | 64.3anthropic |
| SWE-bench Multilingual+Multimodal | — | 80.5anthropic |
| Terminal-Bench | — | 69.4anthropic |
| MCP-Atlas | — | 77.3anthropic |
| Berkeley Function Calling | — | 77.3anthropic |
| OSWorld-Verified | — | 78anthropic |
| BrowseComp | — | 79.3anthropic |
| CharXiv-R | — | 91anthropic |
| DocVQA | — | 93.1anthropic |
| CyberGym | — | 73.1anthropic |
| GDPVal-AA Elo | — | 1753artificial-analysis |
| View Qwen3.5-27B | View Claude Opus 4.7 | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| Qwen3.5-27BCheapest | $0.20 | $0.78 | $0.98 | — |
| Claude Opus 4.7 | $5.00 | $12.50 | $17.50 | +1695% |
Alibaba
Qwen3.5-27B
Qwen3.5-27B is a multimodal llm from Alibaba. Supports up to 262,144 token context window. Achieves 87.5% on MMLU. Available from $0.20/M input tokens.
Anthropic
Claude Opus 4.7
Claude Opus 4.7 is Anthropic's most capable generally available model, with significant improvements in advanced software engineering, agentic tool use, and vision resolution. Achieves 87.6% on SWE-bench Verified and 94.2% on GPQA Diamond. Supports up to 1,000,000 token context window with 3.3x higher-resolution vision than Opus 4.6.
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