Which model is better: DeepSeek V4 Pro or Qwen 3.8 Flash Next?
Qwen 3.8 Flash Next is 87.9% cheaper for input tokens ($0.16 vs. $1.32 per 1M tokens) and $0.47 vs. $3.96 for output tokens (8.2x cost advantage). In terms of operational performance, Qwen 3.8 Flash Next delivers lower response latency at 280ms TTFT (240ms faster than DeepSeek V4 Pro) with 185 vs. 78 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 80.6% for DeepSeek V4 Pro and 91.7% vs. 90.1% 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
DeepSeek V4 Pro
Qwen 3.8 Flash Next
Net Delta / Advantage
Input Cost / 1M Tokens
$1.32
$0.16
Qwen 3.8 Flash Next is 8.3x cheaper
Output Cost / 1M Tokens
$3.96
$0.47
Qwen 3.8 Flash Next (88.1% lower)
Prompt Cache Read / 1M
$0.145
$0.016
Qwen 3.8 Flash Next is 9.1x cheaper
Prompt Cache Write / 1M
$1.32
$0.20
Qwen 3.8 Flash Next is 6.6x cheaper
Context Window (Max Output)
1,024k (128k out)
268k (66k out)
DeepSeek V4 Pro (3.8x larger context)
Avg TTFT Response Latency
520ms
280ms
Qwen 3.8 Flash Next (240ms faster)
Generation Speed (Throughput)
78 tok/s
185 tok/s
Qwen 3.8 Flash Next (+107 tok/s faster)
SWE-bench Verified (Coding)
80.6%
81%
Qwen 3.8 Flash Next (+0.4% lead)
GPQA Diamond (PhD STEM)
90.1%
91.7%
Qwen 3.8 Flash Next (+1.6% lead)
MMLU-Pro (Multi-Discipline)
88.4%
88.4%
Comparable Score
MATH-500 (Quantitative Logic)
97.3%
95.7%
DeepSeek V4 Pro (+1.6% lead)
Inference Value Score (IVR)
67 / 100
85.1 / 100
Qwen 3.8 Flash Next (+18.1 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: DeepSeek V4 Pro 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 $1.32/1M input ($3.96/1M output) for DeepSeek V4 Pro.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V4 Pro 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 520ms TTFT (78 tok/s) for DeepSeek V4 Pro.
How do DeepSeek V4 Pro and Qwen 3.8 Flash Next compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V4 Pro scores 80.6% versus 81% for Qwen 3.8 Flash Next. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V4 Pro scores 90.1% versus 91.7% for Qwen 3.8 Flash Next (and 97.3% vs 95.7% on MATH-500).
When should you choose DeepSeek V4 Pro?
Choose DeepSeek V4 Pro (DeepSeek) for open-weight 1.6T MoE powerhouse designed for cost-effective full-repository code generation, mathematical reasoning, and persistent chain-of-thought multi-step agent workflows — offering a 1,024k context window, 520ms TTFT, and $1.32/1M input pricing ($0.145/1M 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).
