Which model is better: Qwen 3.8 27B or Qwen 3.8 Flash Next?
Qwen 3.8 Flash Next is 20.0% cheaper for input tokens ($0.16 vs. $0.20 per 1M tokens) and $0.47 vs. $0.60 for output tokens (1.2x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (160ms faster than Qwen 3.8 Flash Next) with 140 vs. 185 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 58.4% for Qwen 3.8 27B and 91.7% 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
Qwen 3.8 27B
Qwen 3.8 Flash Next
Net Delta / Advantage
Input Cost / 1M Tokens
$0.20
$0.16
Qwen 3.8 Flash Next is 1.3x cheaper
Output Cost / 1M Tokens
$0.60
$0.47
Qwen 3.8 Flash Next (21.7% lower)
Prompt Cache Read / 1M
$0.050
$0.016
Qwen 3.8 Flash Next is 3.1x cheaper
Prompt Cache Write / 1M
$0.20
$0.20
Identical Cache Write Pricing
Context Window (Max Output)
131k (16k out)
268k (66k out)
Qwen 3.8 Flash Next (2.0x larger context)
Avg TTFT Response Latency
120ms
280ms
Qwen 3.8 27B (160ms faster)
Generation Speed (Throughput)
140 tok/s
185 tok/s
Qwen 3.8 Flash Next (+45 tok/s faster)
SWE-bench Verified (Coding)
58.4%
81%
Qwen 3.8 Flash Next (+22.6% lead)
GPQA Diamond (PhD STEM)
68%
91.7%
Qwen 3.8 Flash Next (+23.7% lead)
MMLU-Pro (Multi-Discipline)
81.2%
88.4%
Qwen 3.8 Flash Next (+7.2% lead)
MATH-500 (Quantitative Logic)
86.4%
95.7%
Qwen 3.8 Flash Next (+9.3% lead)
Inference Value Score (IVR)
74.9 / 100
85.1 / 100
Qwen 3.8 Flash Next (+10.2 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: Qwen 3.8 27B 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 $0.20/1M input ($0.60/1M output) for Qwen 3.8 27B.
Which model has lower TTFT latency and higher tok/s throughput: Qwen 3.8 27B or Qwen 3.8 Flash Next?
Qwen 3.8 27B delivers faster first-token latency at 120ms TTFT (140 tok/s throughput) compared to 280ms TTFT (185 tok/s) for Qwen 3.8 Flash Next.
How do Qwen 3.8 27B and Qwen 3.8 Flash Next compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Qwen 3.8 27B scores 58.4% versus 81% for Qwen 3.8 Flash Next. On GPQA Diamond graduate-level STEM reasoning, Qwen 3.8 27B scores 68% versus 91.7% for Qwen 3.8 Flash Next (and 86.4% vs 95.7% on MATH-500).
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).
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).
