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Disclaimer: Star Stack provides information about European technology services for educational purposes only. Service listings, sovereignty assessments, and recommendations do not constitute legal, financial, or professional advice. We encourage you to verify all information independently and consult appropriate professionals before making technology decisions. Star Stack is not affiliated with any listed services unless explicitly stated.

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vLLM | Star Stack

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vLLM

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vLLM

Name: vLLM
Author: Star Stack

High-throughput, memory-efficient inference engine for LLMs

AI & Machine Learning AI Infrastructure

Visit Website GitHub 93.8K

About

vLLM is an inference and serving engine for large language models that uses PagedAttention to manage memory efficiently. It supports a wide range of open-source models across various hardware platforms including NVIDIA, AMD, and Apple Silicon.

Resources

No migration guide is currently listed for this service.

Suggest a migration guide or report an outdated link.

Sovereignty Score

Recorded assessment version: jurisdiction-ownership-2026-10-04

out of 100

Data completeness36% (Minimal)

Score relies on pessimistic defaults for missing fields

Jurisdictional(56%)

Strong EU base with minimal foreign legal exposure

Legal jurisdiction not specified
No foreign parent provider

Ownership(44%)

Strong EU ownership and control

Bootstrapped (self-funded)
Funding: UC Berkeley research project
Bootstrapped stage
Low acquisition risk (bootstrapped, no investor pressure) (No VC exit timeline, founders retain full control)

More dimensions coming soon

GovernanceComing soon

PortabilityComing soon

LicenseComing soon

CommunityComing soon

How missing data affects scores Submit data corrections

Provider

vLLM Project

Quick Facts

Legal jurisdiction: Unknown
Ownership: Bootstrapped
License: Apache-2.0
Deployment: Self-host
Funding: UC Berkeley research project

Evidence and freshness

Verification date unknown. This assessment needs review.

A score is an assessment of recorded facts. Missing evidence and unresolved ownership can affect the result.

Ownership: other
Statement 12/02/2026, confidence 90%.
Read evidence notes
From enrichment pipeline 2026-02-06_03-32-59_c6_v20-validation