What is SGLang and Why Does It Matter?

Imagine you’re working with big language models (LLMs), but everything feels slow. The responses take forever, and the costs keep going up. What if there was a way to make things faster, cheaper, and more efficient? That’s where SGLang comes in.

SGLang was the first to implement Multi-Token Prediction (MTP) for DeepSeek R1

SGLang is an open-source LLM inference engine that can process 2–5 times more requests than other solutions. This means less waiting, lower bills, and more power. But how does it do that? Let’s break it down.

🚀 Why SGLang is a Big Deal

🔍 RadixAttention & Smart Prompt Handling → 5x Faster for Chat & RAG
Most LLM engines recompute the same prompt again and again for different requests. SGLang is smarter — it reuses the shared parts of prompts, making chatbots and retrieval-augmented generation (RAG) systems up to 5 times faster.

⚡ 3.1x Speed Boost for Structured Output (JSON/XML)
When generating structured data, most models go step by step, even when some parts never change. SGLang skips predictable elements, making JSON and XML outputs much quicker and smoother.

🖥 No More CPU Bottlenecks → Optimized Scheduling
A common issue with LLMs is that the CPU slows things down, even when the GPU is free. SGLang optimizes CPU scheduling, removing these delays and keeping…