[Most Comprehensive Test] Deploying Qwen3.8 27B nvfp4 on V100 with vLLM + dFlash2: Decode speed improved by 3x, Prefill speed improved by 15x
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2026-09-03 12:21:03
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Takeaway conclusions:
1. Qwen3.8 27B has reached the intelligence requirements of enterprise-level AI agents.
2. VLLM already supports V100 adaptation, with generation speeds reaching 50-200 token/s and prefill speeds reaching 1000-4000 token/s, meeting the needs of enterprise-level agents, WorkBuddy, Codex, Trae, and code agents.
3. The NVIDIA V100 offers large memory and low cost. Combined with the software solutions from Shumeng AI, it is currently the most cost-effective Large Language Model deployment solution. Welcome to contact us for private collaboration.
4. Whether NVLink is needed depends on your specific scenario. If only 3-5 people are using it, PCIe is more cost-effective and stable. NVLink offers a 2-3x improvement in multi-concurrent VLLM scenarios, but has little effect in single-concurrent scenarios.
Scenario Topology/Parallel prompt tokens TTFT prefill decode
Long code single path ShumengAIPCIe 8 cards 16457 20.82s 790.39 tok/s 103.56 tok/s
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