vLLM
A high-throughput, memory-efficient open-source engine for serving large language models.
About vLLM
Serving open models at scale wastes GPU memory and money without an optimized engine.
Who it’s for
- Teams self-hosting open models
- ML engineers running inference in production
When to consider it
Consider vLLM when you serve open models on your own GPUs and need throughput.
Tradeoffs & limitations
- Apache-2.0 licensed; you run it on your own hardware or cloud GPUs.
SOTA overview · Documentation-based assessment · Sources & review method
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Comparisons & guides
Sources & review method
Documentation-based assessment · Oct 2, 2026 · Prepared with AI assistance; not a hands-on benchmark.
Checked by SOTA · AI-assisted documentation review. Selection advice is our assessment; verify current requirements for your deployment.
Import history & original evidence
vLLM official website
A high-throughput, memory-efficient open-source engine for serving large language models.
Based on official pages and announcements checked on 2026-10-02. No hands-on test, performance benchmark or popularity ranking is claimed.