vLLM / Inference Serving Stack
Open-source inference engine standard
vLLM (with SGLang, TensorRT-LLM) became the de facto open serving engine that neoclouds and enterprises use to run open models efficiently via PagedAttention. It is strategically important because it commoditizes inference serving, pressuring proprietary API margins and enabling the neocloud business model.
Key technique
PagedAttention
How it fits the stack
vLLM / Inference Serving Stack with what it depends on (above) and what it feeds (below). The figure renders as a crawlable diagram and upgrades to an interactive 3D graph as it scrolls into view.
vLLM / Inference Serving Stack in the AI stack. vLLM / Inference Serving Stack with its immediate upstream dependencies (top) and downstream dependents (bottom) in the AI value chain. Hover a node in 3D, or read the full relationships below.
Graph data (text) — 4 entities, 3 relationships
- vLLM / Inference Serving Stack —depends on→ CUDA / software moat
- Fireworks AI —uses→ vLLM / Inference Serving Stack
- Together AI —uses→ vLLM / Inference Serving Stack
Depends on ↑ · 1