Which model is better: DeepSeek V4 Pro or Qwen 3.8 27B?
Qwen 3.8 27B is 84.8% cheaper for input tokens ($0.20 vs. $1.32 per 1M tokens) and $0.60 vs. $3.96 for output tokens (6.6x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (400ms faster than DeepSeek V4 Pro) with 140 vs. 78 tok/s throughput. DeepSeek V4 Pro leads coding evaluations at 80.6% SWE-bench Verified vs. 58.4% for Qwen 3.8 27B and 90.1% vs. 68.0% 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 27B
Net Delta / Advantage
Input Cost / 1M Tokens
$1.32
$0.20
Qwen 3.8 27B is 6.6x cheaper
Output Cost / 1M Tokens
$3.96
$0.60
Qwen 3.8 27B (84.8% lower)
Prompt Cache Read / 1M
$0.145
$0.050
Qwen 3.8 27B is 2.9x cheaper
Prompt Cache Write / 1M
$1.32
$0.20
Qwen 3.8 27B is 6.6x cheaper
Context Window (Max Output)
1,024k (128k out)
131k (16k out)
DeepSeek V4 Pro (7.8x larger context)
Avg TTFT Response Latency
520ms
120ms
Qwen 3.8 27B (400ms faster)
Generation Speed (Throughput)
78 tok/s
140 tok/s
Qwen 3.8 27B (+62 tok/s faster)
SWE-bench Verified (Coding)
80.6%
58.4%
DeepSeek V4 Pro (+22.2% lead)
GPQA Diamond (PhD STEM)
90.1%
68%
DeepSeek V4 Pro (+22.1% lead)
MMLU-Pro (Multi-Discipline)
88.4%
81.2%
DeepSeek V4 Pro (+7.2% lead)
MATH-500 (Quantitative Logic)
97.3%
86.4%
DeepSeek V4 Pro (+10.9% lead)
Inference Value Score (IVR)
67 / 100
74.9 / 100
Qwen 3.8 27B (+7.9 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).
Which is cheaper: DeepSeek V4 Pro or Qwen 3.8 27B?
Qwen 3.8 27B is cheaper at $0.20/1M input tokens ($0.60/1M 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 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 520ms TTFT (78 tok/s) for DeepSeek V4 Pro.
How do DeepSeek V4 Pro and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V4 Pro scores 80.6% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V4 Pro scores 90.1% versus 68% for Qwen 3.8 27B (and 97.3% vs 86.4% 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 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).
