Qwen 3.8 27B is 98.7% cheaper for input tokens ($0.20 vs. $15.00 per 1M tokens) and $0.60 vs. $60.00 for output tokens (75.0x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (2480ms faster than o1) with 140 vs. 48 tok/s throughput. Qwen 3.8 27B leads coding evaluations at 58.4% SWE-bench Verified vs. 48.9% for o1 and 68.0% vs. 78.0% 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
o1
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
$60.00
$0.60
Qwen 3.8 27B (99.0% lower)
Prompt Cache Read / 1M
$7.500
$0.050
Qwen 3.8 27B is 150.0x cheaper
Prompt Cache Write / 1M
$15.00
$0.20
Qwen 3.8 27B is 75.0x cheaper
Context Window (Max Output)
205k (100k out)
131k (16k out)
o1 (1.6x larger context)
Avg TTFT Response Latency
2600ms
120ms
Qwen 3.8 27B (2480ms faster)
Generation Speed (Throughput)
48 tok/s
140 tok/s
Qwen 3.8 27B (+92 tok/s faster)
SWE-bench Verified (Coding)
48.9%
58.4%
Qwen 3.8 27B (+9.5% lead)
GPQA Diamond (PhD STEM)
78%
68%
o1 (+10.0% lead)
MMLU-Pro (Multi-Discipline)
83.3%
81.2%
o1 (+2.1% lead)
MATH-500 (Quantitative Logic)
96.4%
86.4%
o1 (+10.0% lead)
Inference Value Score (IVR)
37.2 / 100
74.9 / 100
Qwen 3.8 27B (+37.7 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 ($60.00/1M output) for o1.
Which model has lower TTFT latency and higher tok/s throughput: o1 or Qwen 3.8 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.
How do o1 and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, o1 scores 48.9% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, o1 scores 78% versus 68% for Qwen 3.8 27B (and 96.4% vs 86.4% on MATH-500).
When should you choose o1?
Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M 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).
