Open vs closed weights
Some models' weights can be downloaded and run anywhere; others can only be reached through the provider's service.
Read first: Post-training: from predictor to assistant.
D1 · StoryFor young children and total beginners
Some cake recipes are secret: you can only buy the cake at the shop. Others are published so anyone can bake the cake at home.
Closed AI models are like the shop cake. Open-weight models are like the published recipe.
Like: A secret recipe versus a published one.
D2 · PictureFor curious beginners
Closed models are used through an API or app. The provider controls updates, safety measures and how data is handled.
Open-weight models publish the trained weights. Anyone can download them, run them locally, fine-tune them or inspect them, under the terms of their licence, which ranges from permissive to restrictive.
Open weights aren't the same as open source: the training data and full training code are often not released.
Like: A secret recipe versus a published one.
Where it breaks: A published recipe lists every ingredient. Most open-weight models publish the finished weights but not the data or full process, so you can bake the cake but not recreate how the recipe was developed.
D5 · FrontierFor experts
Debates: whether releasing powerful weights is safe given that safeguards can be removed, what should count as 'open source AI', and how quickly open models track the closed frontier.