SHSelfHostIndex

Text Embeddings Inference vs vLLM

A side-by-side comparison of two self-hosted local llm runners options — licensing, setup difficulty, resource needs, and what each one replaces.

Not the right match-up?
TE Text Embeddings Inference Fast inference server for text embedding models VS VL vLLM High-throughput LLM serving engine with PagedAttention
FeatureText Embeddings InferencevLLM
CategoryLocal LLM RunnersLocal LLM Runners
LicenseApache-2.0Apache-2.0
LanguageRustPython
Setup difficultyMediumHard
Min. RAM2,048 MB16,384 MB
Deploymentdockerdocker, kubernetes, bare-metal
GitHub stars★ 4,985★ 88,482
First released20232023
ReplacesOpenAI Embeddings APIOpenAI API

Why pick each one

Choose Text Embeddings Inference if…

  • Released under the Apache-2.0 license
  • First-class Docker support for quick deployment
  • Active community (5k GitHub stars)
  • Written in Rust
Text Embeddings Inference details

Choose vLLM if…

  • Released under the Apache-2.0 license
  • First-class Docker support for quick deployment
  • Kubernetes-ready with Helm charts available
  • Mature project with 88.5k GitHub stars
vLLM details

Frequently asked questions

Is Text Embeddings Inference or vLLM better?

Neither is universally better. vLLM has the larger community, while Text Embeddings Inference is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.

Are Text Embeddings Inference and vLLM free and open-source?

Yes. Text Embeddings Inference is licensed under Apache-2.0 and vLLM under Apache-2.0. Both can be self-hosted at no software cost.

Can I run Text Embeddings Inference and vLLM with Docker?

Text Embeddings Inference: yes. vLLM: yes.

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