OpenFold

weights

open(Apache-2.0 OpenFold3 checkpoints behind an auto-approved form, and OpenFold's own AlphaFold 2-reproduction parameters fetched by repository scripts)

data

open(OpenProteinSet, some 400,000 MSAs and PDB70 template hit files, on the AWS Registry of Open Data)

code

open(train_openfold.py plus a documented end-to-end training guide, not inference alone)

license

Apache-2.0(OSI)

The reason OpenFold exists is the reason it reaches the top rung - it was built to be retrained, and the corpus, the pipeline and the resulting weights all shipped under one OSI license. The evidence is the AlphaFold-2 reproduction SKU specifically - OpenProteinSet on the AWS open-data registry, paired with train_openfold.py and its training guide. OpenFold3-preview ships checkpoints without an equivalent published corpus or pipeline, so it rides on the line's score rather than earning it; the OF2 SKU carries the 5 on its own. The CC-BY-4.0 note in the repository covers DeepMind's parameters, which OpenFold can also load; it does not govern OpenFold's own release.

• https://huggingface.co/api/models/OpenFold/OpenFold3 recorded 2026-09-10

  license: apache-2.0; private: false; gated: auto with the prompt "The OpenFold3-preview model is released under Apache 2.0 license. You will automatically get access to the model after answering the following simple questions"; four checkpoints/*.pt files present.

• https://raw.githubusercontent.com/aqlaboratory/openfold/main/docs/source/original_readme.md recorded 2026-09-10

  "We've publicly released model weights and our training data - some 400,000 MSAs and PDB70 template hit files - under a permissive license. Model weights are available via scripts in this repository while the MSAs are hosted by the Registry of Open Data on AWS."

• https://registry.opendata.aws/openfold/ recorded 2026-09-10

  OpenProteinSet listed on the Registry of Open Data on AWS as a public dataset, cited as OpenFold's training data.

• https://openfold.readthedocs.io/en/latest/Training_OpenFold.html recorded 2026-09-10

  A training guide covering how to train an OpenFold model from the RODA dataset and how to fine-tune it, alongside a separate page on setting up the PDB training set.

• https://raw.githubusercontent.com/aqlaboratory/openfold/main/LICENSE recorded 2026-09-10

  Apache License Version 2.0 body, matching the license the GitHub API reports for the repository.

The gated OpenFold3 endpoint reports zero downloads, which measures the gate rather than the reach, so 3,423 GitHub stars are used as the last-resort signal.

• https://api.github.com/repos/aqlaboratory/openfold recorded 2026-09-10

  stargazers_count: 3423; archived: false; fork: false.

• https://huggingface.co/api/models/OpenFold/OpenFold3 recorded 2026-09-10

  downloads: 0 against likes: 44, on a gated: auto repository.

Two attributes, and the adaptation one is the whole point of the project - the README's first line is that this is a trainable reproduction, and the docs carry a training guide rather than a fine-tuning notebook bolted onto an inference release.

• https://raw.githubusercontent.com/aqlaboratory/openfold/main/README.md recorded 2026-09-10

  "A faithful but trainable PyTorch reproduction of DeepMind's AlphaFold 2", with docs carrying instructions for installation and model inference and training.

• https://raw.githubusercontent.com/aqlaboratory/openfold/main/docs/source/original_readme.md recorded 2026-09-10

  Training data is MSAs and PDB70 template hit files alongside sequence; the repository ships train_openfold.py beside run_pretrained_openfold.py.