00 · IN THREE MINUTES
The answer in three steps
- 1A model is a bundle of artifacts and rights, not a single file.
- 2Open weights may allow local use while withholding training code, data or modification rights.
- 3A meaningful claim should state exactly what is released and under which licence.
01 · THE STACK HAS SEVERAL LAYERS
The stack has several layers
Source code runs training and inference; weights contain learned parameters; configuration describes architecture; data and documentation explain how the system was produced. Each layer can be open, restricted or absent.
02 · ACCESS IS NOT PERMISSION
Access is not permission
A public download may come with limits on commercial use, fields of use or redistribution. Open-source definitions focus on freedoms to use, study, modify and share, not merely on whether a file can be obtained.
The stack has several layers
Source code runs training and inference; weights contain learned parameters; configuration describes architecture; data and documentation explain how the system was produced. Each layer can be open, restricted or absent.
codeAccess is not permission
A public download may come with limits on commercial use, fields of use or redistribution. Open-source definitions focus on freedoms to use, study, modify and share, not merely on whether a file can be obtained.
weightsTraining data is difficult but important
Copyright, privacy and scale can prevent full republication of a dataset. Without sufficient information about data and processing, outsiders may be unable to reproduce or fully audit model behavior.
dataOpenness has degrees
Frameworks score which components and documentation are available. This makes comparisons more informative than a binary badge, especially when weights are open but the recipe is not.
rights + documentation03 · TRAINING DATA IS DIFFICULT BUT IMPORTANT
Training data is difficult but important
Copyright, privacy and scale can prevent full republication of a dataset. Without sufficient information about data and processing, outsiders may be unable to reproduce or fully audit model behavior.
04 · OPENNESS HAS DEGREES
Openness has degrees
Frameworks score which components and documentation are available. This makes comparisons more informative than a binary badge, especially when weights are open but the recipe is not.
05 · OPEN DOES NOT MEAN SAFE OR UNBIASED
Open does not mean safe or unbiased
Transparency can support inspection and adaptation, while the same access can enable misuse. Safety properties, licence freedoms and reproducibility are related questions, not interchangeable ones.
06 · SOURCES AND EVIDENCE
Sources and evidence
Claims are linked to foundational papers, standards or the primary study behind the update.
- 01The Open Source AI Definition 1.0TECHNICAL STANDARD ↗
Supports a defined mechanism, measurement or evidence boundary in this article.
- 02The Model Openness FrameworkTECHNICAL STANDARD ↗
Supports a defined mechanism, measurement or evidence boundary in this article.
