Open-source models release their weights and often their training code publicly (e.g., Llama, Mistral), while closed-source models (e.g., GPT-4, Claude) are ...
Open source means everyone can see how the AI works and use it for free. Closed source means it's a secret that only the company knows.
Open-source AI (like Llama) shares its code and weights so anyone can use or modify it. Closed-source AI (like GPT-4) keeps everything private.
Open-source models release their weights and often their training code publicly (e.g., Llama, Mistral), while closed-source models (e.g., GPT-4, Claude) are only accessible via API.
The spectrum from fully open (weights, data, code published under permissive licenses) to fully closed (API-only access) models, with implications for reproducibility, safety, customization, and competitive dynamics.
A governance and distribution axis ranging from open-weight releases with reproducible training recipes to proprietary API-gated models — intersecting with dual-use risk, responsible disclosure, and the marginal safety cost of capability diffusion.
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