Qwen 3.8 27B is 90.0% cheaper for input tokens ($0.20 vs. $2.00 per 1M tokens) and $0.60 vs. $8.00 for output tokens (10.0x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (1030ms faster than OpenAI o3) with 140 vs. 82 tok/s throughput. OpenAI o3 leads coding evaluations at 71.7% SWE-bench Verified vs. 58.4% for Qwen 3.8 27B and 87.7% 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
OpenAI o3
Qwen 3.8 27B
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$0.20
Qwen 3.8 27B is 10.0x cheaper
Output Cost / 1M Tokens
$8.00
$0.60
Qwen 3.8 27B (92.5% lower)
Prompt Cache Read / 1M
$0.500
$0.050
Qwen 3.8 27B is 10.0x cheaper
Prompt Cache Write / 1M
$2.00
$0.20
Qwen 3.8 27B is 10.0x cheaper
Context Window (Max Output)
205k (100k out)
131k (16k out)
OpenAI o3 (1.6x larger context)
Avg TTFT Response Latency
1150ms
120ms
Qwen 3.8 27B (1030ms faster)
Generation Speed (Throughput)
82 tok/s
140 tok/s
Qwen 3.8 27B (+58 tok/s faster)
SWE-bench Verified (Coding)
71.7%
58.4%
OpenAI o3 (+13.3% lead)
GPQA Diamond (PhD STEM)
87.7%
68%
OpenAI o3 (+19.7% lead)
MMLU-Pro (Multi-Discipline)
89.8%
81.2%
OpenAI o3 (+8.6% lead)
MATH-500 (Quantitative Logic)
98.6%
86.4%
OpenAI o3 (+12.2% lead)
Inference Value Score (IVR)
60.6 / 100
74.9 / 100
Qwen 3.8 27B (+14.3 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 $2.00/1M input ($8.00/1M output) for OpenAI o3.
Which model has lower TTFT latency and higher tok/s throughput: OpenAI o3 or Qwen 3.8 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 1150ms TTFT (82 tok/s) for OpenAI o3.
How do OpenAI o3 and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, OpenAI o3 scores 71.7% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, OpenAI o3 scores 87.7% versus 68% for Qwen 3.8 27B (and 98.6% vs 86.4% on MATH-500).
When should you choose OpenAI o3?
Choose OpenAI o3 (OpenAI) for algorithmic synthesis, mathematical verification, PhD-level scientific research, and multi-step tool planning — offering a 204k context window, 1150ms TTFT, and $2.00/1M input pricing ($0.500/1M 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).
