Ollama Alternatives
Tools that download and run open models locally, like Ollama. On GitHub, Ollama describes itself as: “Get up and running with Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.” Below are the 10 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 Ollama are llama.cpp (100), LocalAI (100) and Jan (98). Ollama itself is still actively maintained (health score 97), so switching is a choice, not a necessity.
Should you switch from Ollama?
Ollama itself is still actively maintained (health score 97), so switching is a choice, not a necessity. Full Ollama record
9 maintained alternatives to Ollama, ranked
| # | Tool | Status | Health | Commits, 91 days | Latest release | Licence | Stars |
|---|---|---|---|---|---|---|---|
| 1 | llama.cppLLM inference in C/C++ | Active | 100 | 1,653 +94% | 15 Oct 2026 | MIT | 132k |
| 2 | LocalAILocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No… | Active | 100 | 1,482 +185% | 2 Oct 2026 | MIT | 49.6k |
| 3 | JanJan is an open source alternative to ChatGPT that runs 100% offline on your computer. | Active | 98 | 1,050 −10% | 9 Oct 2026 | Custom | 45.0k |
| 4 | KoboldCppKoboldCpp - Run GGUF AI models locally with a KoboldAI UI. One File. Zero Install. | Active | 94 | 1,886 +62% | 13 Oct 2026 | AGPL-3.0 | 12.0k |
| 5 | MLX-LMRun LLMs with MLX | Active | 89 | 134 +6% | 16 Oct 2026 | MIT | 7.4k |
| 6 | exoRun frontier AI locally. | Active | 81 | 92 −6% | 23 Apr 2026 | Apache-2.0 | 48.0k |
| 7 | llamafileDistribute and run LLMs with a single file. | Active | 70 | 21 | 15 Sep 2026 | Custom | 26.4k |
| 8 | MLC LLMUniversal LLM Deployment Engine with ML Compilation | Slowing down | 52 | 18 −55% | None on GitHub | Apache-2.0 | 23.3k |
| 9 | TextGenOpen-source desktop app for local LLMs. Text, vision, tool-calling, OpenAI/Anthropic-compatible API. 100% pri… | Slowing down | 18 | 1 −100% | 20 May 2026 | AGPL-3.0 | 47.7k |
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
| Tool | Status | Health | Commits, 91 days | Latest release | Licence | Stars |
|---|---|---|---|---|---|---|
| GPT4AllGPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use. | No recent commits | 0 | 0 | 25 Feb 2025 | MIT | 77.3k |
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
Ollama alternatives: common questions
What is the best alternative to Ollama?
No single tool is best for every project. By maintenance signals on 18 October 2026, the highest-ranked actively maintained alternative is llama.cpp (health score 100, 1,653 commits in the last 91 days). Compare features and the licence before you switch; we have not tested these tools ourselves.
Is Ollama still maintained?
Yes. As of 18 October 2026, Ollama received 372 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 97 out of 100.
Which Ollama alternatives have a permissive licence?
Among the actively maintained alternatives, these use a permissive licence according to GitHub: llama.cpp (MIT), LocalAI (MIT), MLX-LM (MIT), exo (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 Ollama (Tools to run LLMs on your own computer). 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.