Which model is better: GPT-4o Mini or Qwen 3.8 27B?
GPT-4o Mini is 25.0% cheaper for input tokens ($0.15 vs. $0.20 per 1M tokens) and $0.60 vs. $0.60 for output tokens (1.3x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (100ms faster than GPT-4o Mini) with 140 vs. 140 tok/s throughput. Qwen 3.8 27B leads coding evaluations at 58.4% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 68.0% vs. 40.2% 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
GPT-4o Mini
Qwen 3.8 27B
Net Delta / Advantage
Input Cost / 1M Tokens
$0.15
$0.20
GPT-4o Mini is 1.3x cheaper
Output Cost / 1M Tokens
$0.60
$0.60
Identical Output Pricing
Prompt Cache Read / 1M
$0.075
$0.050
Qwen 3.8 27B is 1.5x cheaper
Prompt Cache Write / 1M
$0.15
$0.20
GPT-4o Mini is 1.3x cheaper
Context Window (Max Output)
131k (16k out)
131k (16k out)
Equal Context Window
Avg TTFT Response Latency
220ms
120ms
Qwen 3.8 27B (100ms faster)
Generation Speed (Throughput)
140 tok/s
140 tok/s
Equal Throughput
SWE-bench Verified (Coding)
41%
58.4%
Qwen 3.8 27B (+17.4% lead)
GPQA Diamond (PhD STEM)
40.2%
68%
Qwen 3.8 27B (+27.8% lead)
MMLU-Pro (Multi-Discipline)
68%
81.2%
Qwen 3.8 27B (+13.2% lead)
MATH-500 (Quantitative Logic)
70.2%
86.4%
Qwen 3.8 27B (+16.2% lead)
Inference Value Score (IVR)
67.2 / 100
74.9 / 100
Qwen 3.8 27B (+7.7 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).
GPT-4o Mini is cheaper at $0.15/1M input tokens ($0.60/1M output) compared to $0.20/1M input ($0.60/1M output) for Qwen 3.8 27B.
Which model has lower TTFT latency and higher tok/s throughput: GPT-4o Mini or Qwen 3.8 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 220ms TTFT (140 tok/s) for GPT-4o Mini.
How do GPT-4o Mini and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-4o Mini scores 41% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, GPT-4o Mini scores 40.2% versus 68% for Qwen 3.8 27B (and 70.2% vs 86.4% on MATH-500).
When should you choose GPT-4o Mini?
Choose GPT-4o Mini (OpenAI) for high-volume classification, lightweight RAG chatbots, and structured JSON extraction — offering a 131k context window, 220ms TTFT, and $0.15/1M input pricing ($0.075/1M 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).
