OpenWeights

Open Weights

⚠️ Sample. An AI-generated demo of LLM Wiki Newsroom — the "open source AI" topic is just the example corpus.

Overview

Open weights is a release model in which an AI provider publishes the trained weights and parameters needed to run a model, but typically withholds the training data, detailed data information, and training algorithms. It occupies a middle ground between fully proprietary models and the stricter OpenSourceAI standard: users can run the model and fine-tune it on their own data without paying licensing fees or training from scratch, while the provider keeps its training corpus and know-how as trade secrets. The trade-off is that an open-weights release does not let a user fully understand, reproduce, or audit the underlying model — including its inherent biases — because the training data and algorithms are unavailable. DeepSeek R1 (MIT-licensed weights, January 2025) is a widely cited example.

Connections

• OpenSourceAI — the stricter standard open weights does not meet
• ModelLicensing — open weights is a licensing posture distinct from open source
• FineTuning — the primary capability an open-weights release enables
• TrainingData — the component an open-weights release withholds
• DeepSeek — a prominent open-weights model release