# vLLM reports 954K tokens/s per GPU on SemiAnalysis AgentX with DeepSeek V4.1 Flash

> Original title: Beyond matching DeepInfer's performance, we also put vLLM to the test on @SemiAnalysis_ AgentX with real-world agentic workloads.

- Source: vLLM
- Published: 2026-10-24T23:23:11.000Z
- Bad Influence: https://badinfluence.news/items/e5j4ao81sat4zutnaezf358o3
- Original: https://x.com/vllm_project/status/2114135647040778667

## Summary

vLLM says it ran DeepSeek V4.1 Flash on SemiAnalysis AgentX using P/D disaggregation and Wide-EP on a GB300 NVL72 rack. The company reports 954K tokens/s per GPU total throughput at 196 tokens/s P90 per user, which it calls 7.9× its single-node result. At DeepSeek's off-peak pricing, it reports $38.96 per GPU-hour in revenue. A linked engineering blog describes the optimizations and how to reproduce the results.

## Post

Beyond matching DeepInfer's performance, we also put vLLM to the test on @SemiAnalysis_ AgentX with real-world agentic workloads.

At DeepSeek's off-peak pricing, vLLM delivers $38.96/GPU-hour revenue, with 954K tokens/s/GPU total throughput (cached+input+output) at 196 tokens/s P90 per user.

This is the best DeepSeek-V4.1-Flash result on AgentX ever, powered by recent advancement in vLLM!

Check out our blog for the full optimization story and how to reproduce the results 👇 Enjoy the read.

![](https://badinfluence.news/api/img-proxy?u=https%3A%2F%2Fpbs.twimg.com%2Fmedia%2FHVbrKsdaoAAicF9.jpg&mode=thumb&exp=1793404800&sig=b734df7633e30e30)

## Quoted post @vllm_project

> Scaled out with P/D disaggregation and Wide-EP on a GB300 NVL72 rack, vLLM serves V4.1-Flash on SemiAnalysis AgentX at 954K tokens/s per GPU with 196 tokens/s P90 per user, 7.9× our single-node result.
> 
> Our engineering blog covers the work behind it: https://vllm.ai/blog/2026-10-23-deepseek-v41-flash-pd-wide-ep

https://x.com/vllm_project/status/2114054289488478256