Which model is better: GPT-4o or Qwen 3.8 Flash Next?
Qwen 3.8 Flash Next is 93.6% cheaper for input tokens ($0.16 vs. $2.50 per 1M tokens) and $0.47 vs. $10.00 for output tokens (15.6x cost advantage). In terms of operational performance, Both models demonstrate comparable response latency around 280ms TTFT (100 vs. 185 tok/s). Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 48.0% for GPT-4o and 91.7% vs. 53.6% 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
Qwen 3.8 Flash Next
Net Delta / Advantage
Input Cost / 1M Tokens
$2.50
$0.16
Qwen 3.8 Flash Next is 15.6x cheaper
Output Cost / 1M Tokens
$10.00
$0.47
Qwen 3.8 Flash Next (95.3% lower)
Prompt Cache Read / 1M
$1.250
$0.016
Qwen 3.8 Flash Next is 78.1x cheaper
Prompt Cache Write / 1M
$2.50
$0.20
Qwen 3.8 Flash Next is 12.5x cheaper
Context Window (Max Output)
131k (16k out)
268k (66k out)
Qwen 3.8 Flash Next (2.0x larger context)
Avg TTFT Response Latency
280ms
280ms
Identical Latency
Generation Speed (Throughput)
100 tok/s
185 tok/s
Qwen 3.8 Flash Next (+85 tok/s faster)
SWE-bench Verified (Coding)
48%
81%
Qwen 3.8 Flash Next (+33.0% lead)
GPQA Diamond (PhD STEM)
53.6%
91.7%
Qwen 3.8 Flash Next (+38.1% lead)
MMLU-Pro (Multi-Discipline)
75.9%
88.4%
Qwen 3.8 Flash Next (+12.5% lead)
MATH-500 (Quantitative Logic)
76.6%
95.7%
Qwen 3.8 Flash Next (+19.1% lead)
Inference Value Score (IVR)
47.6 / 100
85.1 / 100
Qwen 3.8 Flash Next (+37.5 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Qwen 3.8 Flash Next is cheaper at $0.16/1M input tokens ($0.47/1M output) compared to $2.50/1M input ($10.00/1M output) for GPT-4o.
Which model has lower TTFT latency and higher tok/s throughput: GPT-4o or Qwen 3.8 Flash Next?
Both GPT-4o and Qwen 3.8 Flash Next deliver comparable response times around 280ms TTFT.
How do GPT-4o and Qwen 3.8 Flash Next compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-4o scores 48% versus 81% for Qwen 3.8 Flash Next. On GPQA Diamond graduate-level STEM reasoning, GPT-4o scores 53.6% versus 91.7% for Qwen 3.8 Flash Next (and 76.6% vs 95.7% on MATH-500).
When should you choose GPT-4o?
Choose GPT-4o (OpenAI) for general enterprise assistants, multimodal customer support, and structured JSON output pipelines — offering a 131k context window, 280ms TTFT, and $2.50/1M input pricing ($1.250/1M 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).
