Free LLM Search Continues: None of the Proposed Models Meet Four Essential Freedoms Requirements

An analysis by Richard Stallman and contributors of six LLMs claimed to be free—Apertus, Moxin, OLMo, Marin, DaVinci, and SmolLM—found that none meet the GNU Project's four essential freedoms because their training data includes non-free or attribution-encumbered material. The authors argue that training data is the functional equivalent of source code, and models relying on datasets like Common Crawl or The Stack, which contain copyrighted works, cannot be considered free. Until a genuinely free LLM is developed, Emacs packages should not recommend such models, and users remain responsible for copyright issues in generated output.

Recent analysis of six LLMs claimed to be "free" reveals that none currently meet the four essential freedoms defined by the GNU Project, primarily because their training data includes non-free or attribution-encumbered material. Richard Stallman and contributors argue that for an LLM to be truly free, its training dataset—the functional equivalent of source code—must consist exclusively of freely licensed data, a standard not met by models like Apertus, Moxin, OLMo, Marin, DaVinci, SmolLM, or OpenCoder due to their reliance on datasets like Common Crawl or The Stack, which contain copyrighted works. Consequently, until a genuinely free LLM is developed, Emacs packages relying on them should not be recommended, and users remain ultimately responsible for copyright issues in generated output regardless of the model's licensing status.