Which model is better: Claude Opus 5.5 or Qwen 3.8 27B?
Qwen 3.8 27B is 95.0% cheaper for input tokens ($0.20 vs. $4.00 per 1M tokens) and $0.60 vs. $20.00 for output tokens (20.0x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (560ms faster than Claude Opus 5.5) with 140 vs. 95 tok/s throughput. Claude Opus 5.5 leads coding evaluations at 89.9% SWE-bench Verified vs. 58.4% for Qwen 3.8 27B and 93.2% vs. 68.0% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.
Zero-Shot RAG Verified
Verified Performance & Unit Economics Delta (12 Dimensions)
Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.
Metric / Dimension
Claude Opus 5.5
Qwen 3.8 27B
Net Delta / Advantage
Input Cost / 1M Tokens
$4.00
$0.20
Qwen 3.8 27B is 20.0x cheaper
Output Cost / 1M Tokens
$20.00
$0.60
Qwen 3.8 27B (97.0% lower)
Prompt Cache Read / 1M
$0.200
$0.050
Qwen 3.8 27B is 4.0x cheaper
Prompt Cache Write / 1M
$5.00
$0.20
Qwen 3.8 27B is 25.0x cheaper
Context Window (Max Output)
1,024k (128k out)
131k (16k out)
Claude Opus 5.5 (7.8x larger context)
Avg TTFT Response Latency
680ms
120ms
Qwen 3.8 27B (560ms faster)
Generation Speed (Throughput)
95 tok/s
140 tok/s
Qwen 3.8 27B (+45 tok/s faster)
SWE-bench Verified (Coding)
89.9%
58.4%
Claude Opus 5.5 (+31.5% lead)
GPQA Diamond (PhD STEM)
93.2%
68%
Claude Opus 5.5 (+25.2% lead)
MMLU-Pro (Multi-Discipline)
92.1%
81.2%
Claude Opus 5.5 (+10.9% lead)
MATH-500 (Quantitative Logic)
98%
86.4%
Claude Opus 5.5 (+11.6% lead)
Inference Value Score (IVR)
57.8 / 100
74.9 / 100
Qwen 3.8 27B (+17.1 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Claude Opus 5.5 (Anthropic) for top-ranked frontier intelligence leader for autonomous multi-step agentic coding, repository-scale migrations, and complex scientific reasoning at a 40% lower workload cost than Opus 5 — offering a 1,024k context window, 680ms TTFT, and $4.00/1M input pricing ($0.200/1M cached reads).
Choose Qwen 3.8 27B (Alibaba Cloud) for high-performance 27B open weights optimized for local deployment, code generation, and low-latency production pipelines — offering a 131k context window, 120ms TTFT, and $0.20/1M input pricing ($0.050/1M cached reads).
Which is cheaper: Claude Opus 5.5 or Qwen 3.8 27B?
Qwen 3.8 27B is cheaper at $0.20/1M input tokens ($0.60/1M output) compared to $4.00/1M input ($20.00/1M output) for Claude Opus 5.5.
Which model has lower TTFT latency and higher tok/s throughput: Claude Opus 5.5 or Qwen 3.8 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 680ms TTFT (95 tok/s) for Claude Opus 5.5.
How do Claude Opus 5.5 and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude Opus 5.5 scores 89.9% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, Claude Opus 5.5 scores 93.2% versus 68% for Qwen 3.8 27B (and 98% vs 86.4% on MATH-500).
When should you choose Claude Opus 5.5?
Choose Claude Opus 5.5 (Anthropic) for top-ranked frontier intelligence leader for autonomous multi-step agentic coding, repository-scale migrations, and complex scientific reasoning at a 40% lower workload cost than Opus 5 — offering a 1,024k context window, 680ms TTFT, and $4.00/1M input pricing ($0.200/1M cached reads).
When should you choose Qwen 3.8 27B?
Choose Qwen 3.8 27B (Alibaba Cloud) for high-performance 27B open weights optimized for local deployment, code generation, and low-latency production pipelines — offering a 131k context window, 120ms TTFT, and $0.20/1M input pricing ($0.050/1M cached reads).
