GoogleReleased Oct 2020Apache 2.0
We don't benchmark Vision Transformer (ViT).
It is an open-weight model from Google under the Apache 2.0 license, and free for commercial use.
Vision Transformer is an image classification model developed by Google Research, first published in October 2020. It applies the transformer architecture directly to sequences of image patches without convolutional layers. Each image is divided into fixed-size patches, linearly projected into embeddings, and processed by a standard transformer encoder with multi-head self-attention. A classification token prepended to the patch sequence aggregates global image information for the final prediction.
Vision Transformer (ViT) is released under the Apache 2.0 license, so it's commercially usable out of the box: you can ship it in closed-source, commercial products, including self-hosted deployments, without paying a license fee or open-sourcing your code. The Vision Transformer (ViT) license is permissive, so no separate commercial license is required.
Apache-2.0 grants an express patent license that terminates if you bring a patent claim over the work, and it disclaims warranties. Validate Vision Transformer (ViT) on your own data before you depend on it in production.
Read the full Apache 2.0 license ↗This is the straightforward case: a permissive license is the best technical solution and you are free to deploy Vision Transformer (ViT) commercially without open-sourcing your own code.
Do not hesitate to reach out with questions for your commercial project. Our team will help you start solving business problems on the first call. See Roboflow commercial licensing for the models included in each plan.
Talk to salesThis model is released under the Apache License 2.0, a permissive open-source license that allows commercial use, modification, distribution, and patent use.
Yes. Under the terms of the Apache 2.0 license, you can freely use this model for commercial purposes, including in proprietary products. You must retain the copyright notice and disclaimers when redistributing.
License information is provided as a guide and is not legal advice.
Other models worth comparing for similar use cases.