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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →A closed AI model is one whose trained weights are not publicly available to download and remain under the developer’s control. People may still use it through a hosted app or API: access to a service is not the same as access to the model’s weights.
What does “closed AI model” mean?
In common usage, “closed AI model” usually means a closed-weight model: the developer has not released the model’s learned numerical parameters for public download. The weights are the values the model uses to produce outputs; code interprets and applies them.
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The label describes how the underlying model assets are released and controlled. It does not mean the model cannot be used, or that every related component is secret. A developer might publish documentation or a behavior specification while keeping the weights private.
Does API or app access make a model open?
No. A provider can let users interact with a model through a website, app, or API while retaining its weights. In that arrangement, the provider operates the model and grants access to its capabilities, but users do not receive the model itself to download and run.
Conversely, public weights do not automatically make a model fully open-source. Training data, training code, inference code, and other development materials may remain unavailable. A license or usage policy may also limit what users can do with released weights.
How open or closed can a model be?
Release is better understood as a set of separate choices than as a single yes-or-no label. Stanford HAI’s framework distinguishes levels such as no external access, hosted use, API access, fine-tuning access, downloadable weights, and releases that also provide data and code. A model can be open in one respect and closed in another.
- Weights: Are they publicly downloadable, available only to selected users, or not released?
- Access channel: Is use limited to a hosted app or API, or can users run the model themselves?
- Other assets: Are training data, training or inference code, documentation, and evaluation materials available?
- Terms: What do the license and usage policy allow, including commercial use and redistribution?
- Deployment: Who operates the model, and where is input data processed?
Examples: a closed service and an open-weight release
OpenAI has described its most powerful models as services whose weights it does not distribute beyond OpenAI and Microsoft, with third parties accessing them through APIs. That is a provider’s description of its own service arrangement, not a rule about every model or provider.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchOpenAI’s gpt-oss documentation describes gpt-oss-120b and gpt-oss-20b as open-weight models, with weights available under Apache 2.0 and an additional usage policy. The documentation says they are not served through the OpenAI API or ChatGPT and can be run on infrastructure users control or through hosting providers. These are product details that can change; check the provider’s current documentation when making a deployment decision.
In an August 5, 2025 article, OpenAI presented open-weight and closed models as potentially complementary, citing local control and data-residency needs as reasons open weights can matter. That is the company’s position, not a universal conclusion about which approach is preferable.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should you check when comparing models?
- Confirm weight availability. Look for an explicit statement that weights can be downloaded, and note whether access is public or restricted.
- Separate access from release. An API or chat interface lets you use a model but does not establish that its weights are available.
- Check what else is published. Do not assume public weights include the training data, full code, or complete development recipe.
- Read the terms. Check the license and any usage policy for restrictions on use, modification, and redistribution.
- Identify who runs it. A hosted model leaves operation with the provider; downloadable weights may allow self-hosting, subject to technical requirements and license terms.
These checks are more informative than treating “open” or “closed” as a complete description. Neither label alone establishes that a model is safer, more accurate, cheaper, or more secure.
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