Which model is better: DeepSeek V3 or Qwen 3.8 27B?
DeepSeek V3 is 30.0% cheaper for input tokens ($0.14 vs. $0.20 per 1M tokens) and $0.28 vs. $0.60 for output tokens (1.4x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (290ms faster than DeepSeek V3) with 140 vs. 78 tok/s throughput. Qwen 3.8 27B leads coding evaluations at 58.4% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 68.0% vs. 59.1% 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 V3
Qwen 3.8 27B
Net Delta / Advantage
Input Cost / 1M Tokens
$0.14
$0.20
DeepSeek V3 is 1.4x cheaper
Output Cost / 1M Tokens
$0.28
$0.60
DeepSeek V3 (53.3% lower)
Prompt Cache Read / 1M
$0.014
$0.050
DeepSeek V3 is 3.6x cheaper
Prompt Cache Write / 1M
$0.14
$0.20
DeepSeek V3 is 1.4x cheaper
Context Window (Max Output)
131k (8k out)
131k (16k out)
Equal Context Window
Avg TTFT Response Latency
410ms
120ms
Qwen 3.8 27B (290ms faster)
Generation Speed (Throughput)
78 tok/s
140 tok/s
Qwen 3.8 27B (+62 tok/s faster)
SWE-bench Verified (Coding)
42%
58.4%
Qwen 3.8 27B (+16.4% lead)
GPQA Diamond (PhD STEM)
59.1%
68%
Qwen 3.8 27B (+8.9% lead)
MMLU-Pro (Multi-Discipline)
75.9%
81.2%
Qwen 3.8 27B (+5.3% lead)
MATH-500 (Quantitative Logic)
90.2%
86.4%
DeepSeek V3 (+3.8% lead)
Inference Value Score (IVR)
75 / 100
74.9 / 100
DeepSeek V3 (+0.1 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).
DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M output) compared to $0.20/1M input ($0.60/1M output) for Qwen 3.8 27B.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V3 or Qwen 3.8 27B?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 410ms TTFT (78 tok/s) for DeepSeek V3.
How do DeepSeek V3 and Qwen 3.8 27B compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 58.4% for Qwen 3.8 27B. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 68% for Qwen 3.8 27B (and 90.2% vs 86.4% on MATH-500).
When should you choose DeepSeek V3?
Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M 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).
