LaunchpadHQ

vLLM

by Open Source (UC Berkeley)

The Launchpad take

Verdict

High-throughput LLM serving engine

High-performance LLM serving; production inference; PagedAttention for throughput; batch processing

Best for

ML engineersplatform teamscompanies serving LLMs at scaleGPU server operators

Quick facts

Free tier
Completely free and open-source (Apache 2.0)
Starting price
Free
Platforms
local
Company
Open Source (UC Berkeley)
Ready to try vLLM? Start with the getting-started guide.

Pricing

PlanPriceKey limits
FreeFreeNone (hardware-limited; designed for GPU servers)

Key capabilities

Works with

  • Text
  • embeddings

Outputs

  • OpenAI-compatible API responses
  • batch outputs

Get it

How to use vLLM on phones and tablets.

  • Mobile web: Works in a mobile browser (responsive or dedicated mobile site).

Technical details

Offline
Yes
API
Yes
Languages
Multilingual (depends on model)
Difficulty
Advanced
Privacy
High
Time to productivity
2 hours
Upgrade when
N/A (fully free)
Integrations
OpenAI-compatible API, Hugging Face models, Ray (distributed), Kubernetes
more

LangChain, major frameworks

Alternatives

LocalAI

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OpenAI API-compatible local inference

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Free-plan details

Completely free and open-source (MIT)

Meet the tool

Related in Local & Open-Source AI

Tutorials