vLLM deployment

1. Introduction

In this guide, we’ll explore the most cost-effective way to deploy a large language model (LLM) from a local environment to a server.

One of the biggest challenges in this process is designing a robust application that can handle multiple concurrent requests on limited hardware while maintaining high performance.

To tackle this, we’ll dive into vLLM, a powerful solution for optimizing inference efficiency.

2. Key Topics

This guide is structured around two main topics:

  1. Understanding vLLM – How vLLM works, its benefits, and real-world applications in optimizing LLM inference.
  2. Deploying DeepSeek R1 Distill on vLLM – A step-by-step guide on implementing a distilled model with vLLM to achieve high efficiency at low cost.

Let’s get started and see how vLLM can supercharge LLM inference!