Which model is better: GPT-4o Mini or Qwen 3.8 Flash Next?
GPT-4o Mini is 6.2% cheaper for input tokens ($0.15 vs. $0.16 per 1M tokens) and $0.60 vs. $0.47 for output tokens (1.1x cost advantage). In terms of operational performance, GPT-4o Mini delivers lower response latency at 220ms TTFT (60ms faster than Qwen 3.8 Flash Next) with 140 vs. 185 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 91.7% 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 Flash Next
Net Delta / Advantage
Input Cost / 1M Tokens
$0.15
$0.16
GPT-4o Mini is 1.1x cheaper
Output Cost / 1M Tokens
$0.60
$0.47
Qwen 3.8 Flash Next (21.7% lower)
Prompt Cache Read / 1M
$0.075
$0.016
Qwen 3.8 Flash Next is 4.7x cheaper
Prompt Cache Write / 1M
$0.15
$0.20
GPT-4o Mini is 1.3x cheaper
Context Window (Max Output)
131k (16k out)
268k (66k out)
Qwen 3.8 Flash Next (2.0x larger context)
Avg TTFT Response Latency
220ms
280ms
GPT-4o Mini (60ms faster)
Generation Speed (Throughput)
140 tok/s
185 tok/s
Qwen 3.8 Flash Next (+45 tok/s faster)
SWE-bench Verified (Coding)
41%
81%
Qwen 3.8 Flash Next (+40.0% lead)
GPQA Diamond (PhD STEM)
40.2%
91.7%
Qwen 3.8 Flash Next (+51.5% lead)
MMLU-Pro (Multi-Discipline)
68%
88.4%
Qwen 3.8 Flash Next (+20.4% lead)
MATH-500 (Quantitative Logic)
70.2%
95.7%
Qwen 3.8 Flash Next (+25.5% lead)
Inference Value Score (IVR)
67.2 / 100
85.1 / 100
Qwen 3.8 Flash Next (+17.9 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Which is cheaper: GPT-4o Mini or Qwen 3.8 Flash Next?
GPT-4o Mini is cheaper at $0.15/1M input tokens ($0.60/1M output) compared to $0.16/1M input ($0.47/1M output) for Qwen 3.8 Flash Next.
Which model has lower TTFT latency and higher tok/s throughput: GPT-4o Mini or Qwen 3.8 Flash Next?
GPT-4o Mini delivers faster first-token latency at 220ms TTFT (140 tok/s throughput) compared to 280ms TTFT (185 tok/s) for Qwen 3.8 Flash Next.
How do GPT-4o Mini and Qwen 3.8 Flash Next compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-4o Mini scores 41% versus 81% for Qwen 3.8 Flash Next. On GPQA Diamond graduate-level STEM reasoning, GPT-4o Mini scores 40.2% versus 91.7% for Qwen 3.8 Flash Next (and 70.2% vs 95.7% 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 Flash Next?
Choose Qwen 3.8 Flash Next (Alibaba Cloud) for next-generation open-weight multimodal MoE activating only 6B parameters per token for ultra-low-cost enterprise office automation, tool calling, and multilingual repository engineering — offering a 268k context window, 280ms TTFT, and $0.16/1M input pricing ($0.016/1M cached reads).
