Field noteOct 24, 20261 min read1 source

Full engineering writeup covers DEP2 prefill, Wide-EP decode, and CPU overhead fixes.

In one minute

vLLM published an engineering write-up on serving DeepSeek-V4.1-Flash with prefill/decode disaggregation and Wide-EP decode across an NVIDIA GB300 NVL72 rack.

What changed: The writeup adds rack-scale GB300 results, DEP2 prefill and Wide-EP/EPLB scaling details, CPU-overhead fixes, and a 826 tokens/s single-user decode path.

The team reports 954,000 tokens per second per GPU on the SemiAnalysis AgentX benchmark, with P90 per-user throughput of 196 tokens per second. It describes this as a 7.9x increase over its earlier aggregated single-node result, and cites DeepSeek off-peak pricing of $38.96 per GPU-hour. A specialized small-batch decode path reached 826 tokens per second for one user.

For comparison, vLLM says its GB200 decode results were within 6% of DeepInfer's published throughput across batches of 8 to 256 at 131K context. Its prefill comparison uses different hardware and configurations, so the post says it does not treat the difference as an engine-to-engine speedup.

The post attributes the work to DEP2 prefill, Wide-EP decode, expert parallel load balancing, and reductions in CPU overhead. It does not establish equivalent performance for other models, workloads, hardware, pricing tiers, or production deployments.

Evidence / sources

  1. 1vllm.ai/blog/2026-10-23-deepseek-v41-flash-pd-wide-ep
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