Open-weight Model
Model Bobot Terbuka
A model whose weights you can download and run yourself, under a licence that says what you may do.
An open-weight model is one whose trained parameters are published, so you can download them, run them on your own hardware, and modify them. The licence attached to those weights says what you are allowed to do: commercial use, redistribution, or neither.
Open weights and open source are different claims. Publishing weights makes the model inspectable and runnable; it does not make the training data or the training code public, and for most licences it does not make the model free of use restrictions.
For an organisation, the appeal is control: no per-token bill, no data leaving the network, and the ability to fine-tune for a specific domain. The trade is that you now own the operations, and the quality gap against the newest hosted model is usually real for difficult tasks.
Related terms
Local LLM
Running the model on your own machine or server, with no provider in the loop.
Quantization
Storing weights in fewer bits so a model runs with less memory and cost.
Model
The trained file of learned parameters that turns input into output.
IP
Who owns what the model produced, and what it was trained on.
Fine-tuning
Further training of an existing model on your own data to shape its behaviour.
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