Which model is better: Claude 4 Opus or Qwen 3.8 27B?
Qwen 3.8 27B is 98.7% cheaper for input tokens ($0.20 vs. $15.00 per 1M tokens) and $0.60 vs. $75.00 for output tokens (75.0x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (800ms faster than Claude 4 Opus) with 140 vs. 46 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 58.4% for Qwen 3.8 27B and 87.1% 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 4 Opus
Qwen 3.8 27B
Net Delta / Advantage
Input Cost / 1M Tokens
$15.00
$0.20
Qwen 3.8 27B is 75.0x cheaper
Output Cost / 1M Tokens
$75.00
$0.60
Qwen 3.8 27B (99.2% lower)
Prompt Cache Read / 1M
$1.500
$0.050
Qwen 3.8 27B is 30.0x cheaper
Prompt Cache Write / 1M
$18.75
$0.20
Qwen 3.8 27B is 93.8x cheaper
Context Window (Max Output)
205k (64k out)
131k (16k out)
Claude 4 Opus (1.6x larger context)
Avg TTFT Response Latency
920ms
120ms
Qwen 3.8 27B (800ms faster)
Generation Speed (Throughput)
46 tok/s
140 tok/s
Qwen 3.8 27B (+94 tok/s faster)
SWE-bench Verified (Coding)
77.2%
58.4%
Claude 4 Opus (+18.8% lead)
GPQA Diamond (PhD STEM)
87.1%
68%
Claude 4 Opus (+19.1% lead)
MMLU-Pro (Multi-Discipline)
91.8%
81.2%
Claude 4 Opus (+10.6% lead)
MATH-500 (Quantitative Logic)
98.1%
86.4%
Claude 4 Opus (+11.7% lead)
Inference Value Score (IVR)
43.6 / 100
74.9 / 100
Qwen 3.8 27B (+31.3 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
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).
Qwen 3.8 27B is cheaper at $0.20/1M input tokens ($0.60/1M output) compared to $15.00/1M input ($75.00/1M output) for Claude 4 Opus.
Which model has lower TTFT latency and higher tok/s throughput: Claude 4 Opus or Qwen 3.8 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 920ms TTFT (46 tok/s) for Claude 4 Opus.
How do Claude 4 Opus and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 4 Opus scores 77.2% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, Claude 4 Opus scores 87.1% versus 68% for Qwen 3.8 27B (and 98.1% vs 86.4% on MATH-500).
When should you choose Claude 4 Opus?
Choose Claude 4 Opus (Anthropic) for mission-critical R&D, long-horizon autonomous coding tasks, complex theorem proving, and executive strategic synthesis — offering a 204k context window, 920ms TTFT, and $15.00/1M input pricing ($1.500/1M 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).
