Which model is better: OpenAI o4-mini or Qwen 3.8 Flash Next?
Qwen 3.8 Flash Next is 85.5% cheaper for input tokens ($0.16 vs. $1.10 per 1M tokens) and $0.47 vs. $4.40 for output tokens (6.9x cost advantage). In terms of operational performance, Qwen 3.8 Flash Next delivers lower response latency at 280ms TTFT (400ms faster than OpenAI o4-mini) with 185 vs. 125 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 68.1% for OpenAI o4-mini and 91.7% vs. 81.4% 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 o4-mini
Qwen 3.8 Flash Next
Net Delta / Advantage
Input Cost / 1M Tokens
$1.10
$0.16
Qwen 3.8 Flash Next is 6.9x cheaper
Output Cost / 1M Tokens
$4.40
$0.47
Qwen 3.8 Flash Next (89.3% lower)
Prompt Cache Read / 1M
$0.275
$0.016
Qwen 3.8 Flash Next is 17.2x cheaper
Prompt Cache Write / 1M
$1.10
$0.20
Qwen 3.8 Flash Next is 5.5x cheaper
Context Window (Max Output)
205k (100k out)
268k (66k out)
Qwen 3.8 Flash Next (1.3x larger context)
Avg TTFT Response Latency
680ms
280ms
Qwen 3.8 Flash Next (400ms faster)
Generation Speed (Throughput)
125 tok/s
185 tok/s
Qwen 3.8 Flash Next (+60 tok/s faster)
SWE-bench Verified (Coding)
68.1%
81%
Qwen 3.8 Flash Next (+12.9% lead)
GPQA Diamond (PhD STEM)
81.4%
91.7%
Qwen 3.8 Flash Next (+10.3% lead)
MMLU-Pro (Multi-Discipline)
85.6%
88.4%
Qwen 3.8 Flash Next (+2.8% lead)
MATH-500 (Quantitative Logic)
97.8%
95.7%
OpenAI o4-mini (+2.1% lead)
Inference Value Score (IVR)
63.7 / 100
85.1 / 100
Qwen 3.8 Flash Next (+21.4 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: OpenAI o4-mini or Qwen 3.8 Flash Next?
Qwen 3.8 Flash Next is cheaper at $0.16/1M input tokens ($0.47/1M output) compared to $1.10/1M input ($4.40/1M output) for OpenAI o4-mini.
Which model has lower TTFT latency and higher tok/s throughput: OpenAI o4-mini or Qwen 3.8 Flash Next?
Qwen 3.8 Flash Next delivers faster first-token latency at 280ms TTFT (185 tok/s throughput) compared to 680ms TTFT (125 tok/s) for OpenAI o4-mini.
How do OpenAI o4-mini and Qwen 3.8 Flash Next compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, OpenAI o4-mini scores 68.1% versus 81% for Qwen 3.8 Flash Next. On GPQA Diamond graduate-level STEM reasoning, OpenAI o4-mini scores 81.4% versus 91.7% for Qwen 3.8 Flash Next (and 97.8% vs 95.7% on MATH-500).
When should you choose OpenAI o4-mini?
Choose OpenAI o4-mini (OpenAI) for automated PR review, high-volume agentic coding loops, SQL/data analysis, and visual document reasoning — offering a 204k context window, 680ms TTFT, and $1.10/1M input pricing ($0.275/1M 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).
