vLLM Alternatives

LLM inference servers Data checked 18 Oct 2026, 22:50 UTC

Tools that serve open models behind an API for many users, like vLLM. On GitHub, vLLM describes itself as: “A high-throughput and memory-efficient inference and serving engine for LLMs”. Below are the 5 other open-source tools we track for the same job, ranked by live maintenance data from GitHub.

Short answer: Ranked by our health score from public GitHub data on 18 October 2026, the most actively maintained alternatives to vLLM are SGLang (100), LocalAI (100) and TensorRT-LLM (97). vLLM itself is still actively maintained (health score 100), so switching is a choice, not a necessity.

Should you switch from vLLM?

StatusActive
Health score100
Commits, 91 days4,4112,767 a year earlier
Last commit18 Oct 2026
LicenceApache-2.0

vLLM itself is still actively maintained (health score 100), so switching is a choice, not a necessity. Full vLLM record

Highest health score SGLang Health score 100 out of 100
Most development activity SGLang 4,904 commits in the last 91 days
Best-maintained with a permissive licence SGLang Apache-2.0 licence, health score 100
Most recent release LocalAI v4.11.0, published 2 Oct 2026

4 maintained alternatives to vLLM, ranked

#ToolStatusHealthCommits, 91 daysLatest releaseLicenceStars
1SGLangSGLang is a high-performance serving framework for large language models and multimodal models.Active1004,904 +155%2 Oct 2026Apache-2.037.3k
2LocalAILocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No…Active1001,482 +185%2 Oct 2026MIT49.6k
3TensorRT-LLMTensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and support…Active972,367 +79%20 Apr 2026Custom14.9k
4LMDeployLMDeploy is a toolkit for compressing, deploying, and serving LLMs.Active89148 −5%28 Sep 2026Apache-2.08.1k

Ranked by status first, then health score (0 to 100). Commits are counted on each project’s default branch; the percentage compares with the same 91 days a year earlier. Stars are bookmarks, not users.

Also in this group, but stopped or in maintenance

ToolStatusHealthCommits, 91 daysLatest releaseLicenceStars
TGI (Hugging Face)Large Language Model Text Generation InferenceArchived00 −100%19 Dec 2025Apache-2.010.9k

These projects are archived, in maintenance mode or had no commits in the last 91 days. They may still work, but they are a risky choice for a new project.

Compare and explore

TGI (Hugging Face) alternatives

vLLM alternatives: common questions

What is the best alternative to vLLM?

No single tool is best for every project. By maintenance signals on 18 October 2026, the highest-ranked actively maintained alternative is SGLang (health score 100, 4,904 commits in the last 91 days). Compare features and the licence before you switch; we have not tested these tools ourselves.

Is vLLM still maintained?

Yes. As of 18 October 2026, vLLM received 4,411 commits in the last 91 days and its latest commit is from 18 October 2026, and no maintenance notice was found. Its health score is 100 out of 100.

Which vLLM alternatives have a permissive licence?

Among the actively maintained alternatives, these use a permissive licence according to GitHub: SGLang (Apache-2.0), LocalAI (MIT), LMDeploy (Apache-2.0). Always read the licence file itself before commercial use.

How are these alternatives chosen and ranked?

We list the tools we track that do the same job as vLLM (LLM inference servers). They are ranked by maintenance status first (active, slowing down, stopped) and by our health score second. The score combines commit activity, the trend against last year, the date of the last commit, the last release and merged pull requests, all from GitHub. It does not measure features, speed, quality or security.

How this works: we group tools by the job they do and rank the ones we track with public GitHub data (commits on the default branch, releases, merged pull requests, archived flag, and maintenance notices in the README), refreshed automatically. We have not tested these tools ourselves, so the ranking says how well each project is maintained, not which one has the features you need.