Free Lesson
Inside an LLM Serving Engine: How vLLM and SGLang Work
60 min
Oct 30, 2026 10:00 PM
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What you'll learn
Follow one request through the engine
Trace a prompt from the API server to the scheduler, the KV cache manager and the model runner, and back as tokens.
See where vLLM and SGLang differ
How each engine schedules requests and manages the KV cache, from block tables to a radix tree, and why it matters.
Know which engine fits your workload
Where each engine is stronger, from chat and agents to many models and GPUs, and how to decide with your own numbers.
Why this topic matters
vLLM and SGLang look alike from the outside: you send a prompt and tokens stream back. Inside, they make different choices about scheduling, memory and caching, and those choices decide how many users one GPU can serve. We follow one request through each engine, from the HTTP call to the last token, and see exactly where the two differ. No prior engine knowledge needed. The second of three free lessons before our vLLM and SGLang bootcamp.
