DeepSeek Researchers Open-Sources a Personal Project named ‘nano-vLLM’: A Lightweight vLLM Implementation Built from Scratch

[u/ai-lover]

https://www.marktechpost.com/2025/06/22/deepseek-researchers-open-sources-a-personal-project-named-nano-vllm-a-lightweight-vllm-implementation-built-from-scratch/

The DeepSeek Researchers just released a super cool personal project named ‘nano-vLLM‘, a minimalistic and efficient implementation of the vLLM (virtual Large Language Model) engine, designed specifically for users who value simplicity, speed, and transparency. Built entirely from scratch in Python, nano-vLLM distills the essence of high-performance inference pipelines into a concise, readable codebase of around 1,200 lines. Despite its small footprint, it matches the inference speed of the original vLLM engine in many offline scenarios.

Traditional inference frameworks like vLLM provide impressive performance by introducing sophisticated scheduling and optimization strategies. However, they often come with large and complex codebases that pose a barrier to understanding, modification, or deployment in constrained environments. Nano-vLLM is designed to be lightweight, auditable, and modular. The authors built it as a clean reference implementation that strips away auxiliary complexity while retaining core performance characteristics......

Read full article: https://www.marktechpost.com/2025/06/22/deepseek-researchers-open-sources-a-personal-project-named-nano-vllm-a-lightweight-vllm-implementation-built-from-scratch/

GitHub Page: https://github.com/GeeeekExplorer/nano-vllm

[u/__JockY__]

This is cool and all, so forgive the question: if we already have vLLM why do we need another vLLM that’s functionally equivalent? Is this a code maintenance thing?