Which model is better: Claude 3.5 Haiku or Qwen 3.8 27B?
Qwen 3.8 27B is 75.0% cheaper for input tokens ($0.20 vs. $0.80 per 1M tokens) and $0.60 vs. $4.00 for output tokens (4.0x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (70ms faster than Claude 3.5 Haiku) with 140 vs. 130 tok/s throughput. Qwen 3.8 27B leads coding evaluations at 58.4% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 68.0% vs. 41.6% 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 3.5 Haiku
Qwen 3.8 27B
Net Delta / Advantage
Input Cost / 1M Tokens
$0.80
$0.20
Qwen 3.8 27B is 4.0x cheaper
Output Cost / 1M Tokens
$4.00
$0.60
Qwen 3.8 27B (85.0% lower)
Prompt Cache Read / 1M
$0.080
$0.050
Qwen 3.8 27B is 1.6x cheaper
Prompt Cache Write / 1M
$1.00
$0.20
Qwen 3.8 27B is 5.0x cheaper
Context Window (Max Output)
205k (8k out)
131k (16k out)
Claude 3.5 Haiku (1.6x larger context)
Avg TTFT Response Latency
190ms
120ms
Qwen 3.8 27B (70ms faster)
Generation Speed (Throughput)
130 tok/s
140 tok/s
Qwen 3.8 27B (+10 tok/s faster)
SWE-bench Verified (Coding)
40.6%
58.4%
Qwen 3.8 27B (+17.8% lead)
GPQA Diamond (PhD STEM)
41.6%
68%
Qwen 3.8 27B (+26.4% lead)
MMLU-Pro (Multi-Discipline)
71%
81.2%
Qwen 3.8 27B (+10.2% lead)
MATH-500 (Quantitative Logic)
69.4%
86.4%
Qwen 3.8 27B (+17.0% lead)
Inference Value Score (IVR)
52.4 / 100
74.9 / 100
Qwen 3.8 27B (+22.5 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).
Which is cheaper: Claude 3.5 Haiku or Qwen 3.8 27B?
Qwen 3.8 27B is cheaper at $0.20/1M input tokens ($0.60/1M output) compared to $0.80/1M input ($4.00/1M output) for Claude 3.5 Haiku.
Which model has lower TTFT latency and higher tok/s throughput: Claude 3.5 Haiku or Qwen 3.8 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 190ms TTFT (130 tok/s) for Claude 3.5 Haiku.
How do Claude 3.5 Haiku and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.5 Haiku scores 40.6% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, Claude 3.5 Haiku scores 41.6% versus 68% for Qwen 3.8 27B (and 69.4% vs 86.4% on MATH-500).
When should you choose Claude 3.5 Haiku?
Choose Claude 3.5 Haiku (Anthropic) for rapid customer-facing chat, sub-agent routing, and real-time code autocomplete — offering a 204k context window, 190ms TTFT, and $0.80/1M input pricing ($0.080/1M 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).
