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Alibaba Cloud (Qwen)
Qwen3.8-27B
VS
DeepSeek
DeepSeek V4 Flash 0731
Analysis By: The WhichLLMModel Editorial Team|Updated: June 2026
Live Hardware Compatibility Simulator
GPU Dedicated VRAM16 GB
System Host RAM32 GB
Qwen3.8-27BPartial CPU Offload
VRAM Footprint (Q4):18.27 GB
Active GPU Load:14.45 GB
DeepSeek V4 Flash 0731OOM / Exceeds Limit
VRAM Footprint (Q4):145.97 GB
Active GPU Load:12.61 GB
Hardware & Architecture Shootout Matrix
| Metric / Spec | Qwen3.8-27B | DeepSeek V4 Flash 0731 |
|---|---|---|
| Parameter Scale | 27B Parameters | 284B Parameters |
| Attention Architecture | GQA + DeltaNet Linear | Standard GQA / MHA |
| Max Context Window | 262.14k | 1.05M |
| Available GGUF Quants | 3 Quant Formats | 2 Quant Formats |
| Full Model Page | Hardware Details | Hardware Details |
Intelligence & Benchmark Head-to-Head
Coding Benchmark (SWE-bench / HumanEval)
Qwen3.8-27B61.7%
DeepSeek V4 Flash 073154.4%
Reasoning Benchmark (GPQA / MMLU)
Qwen3.8-27B89.2%
DeepSeek V4 Flash 0731N/A%
Frequently Asked Questions about Qwen3.8-27B vs DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 is cheaper than Qwen3.8-27B. DeepSeek V4 Flash 0731 has a blended cost of $NaN/1M tokens, which is about 1.0x cheaper than Qwen3.8-27B at $NaN/1M tokens.
For coding tasks, Qwen3.8-27B scores 61.7% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while DeepSeek V4 Flash 0731 scores 54.4% on deep-swe (frontier deep software engineering and end-to-end repository problem solving).
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