AlphaGenome
GoogleAlphaGenome is Google DeepMind's genomic sequence model for predicting gene expression, splicing, chromatin features, contact maps, and variant effects. It accepts sequences up to one million base pairs and produces most outputs at single-base-pair resolution through an API, a precomputed Atlas, and a gated downloadable checkpoint.
The repository documents both API and local-checkpoint surfaces; the downloadable model remains subject to separate non-commercial terms. Verified 2026-09-10 via the Hugging Face API, model terms, and Google DeepMind repository.
Openness
2 high confidence- weights
- open(gated downloadable checkpoint files)
- data
- closed(training corpus not released)
- code
- partial(Apache-2.0 API client, examples, and notebook
- license
- AlphaGenome-Model-Terms(non-commercial use only)
The checkpoint is now downloadable after accepting terms, correcting the original API-only roster claim, but the terms prohibit commercial use and therefore cap the score at restricted.
- https://huggingface.co/api/models/google/alphagenome-all-folds recorded 2026-09-10
gated: auto; private: false; license_name: alphagenome; checkpoint metadata, manifests, and weight shards present; gate says non-commercial use only.
- https://raw.githubusercontent.com/google-deepmind/alphagenome/main/README.md recorded 2026-09-10
Repository supplies an Apache-2.0 API client and examples, describes hosted predictions and Atlas, and publishes no pretraining code or corpus.
- https://deepmind.google.com/science/alphagenome/model-terms recorded 2026-09-10
AlphaGenome model terms govern the downloadable model and limit the grant to non-commercial use.
Adoption
2 medium confidenceThe gated Hub endpoint reports zero downloads, so 2,080 GitHub stars are used as the last-resort signal.
- https://api.github.com/repos/google-deepmind/alphagenome recorded 2026-09-10
stargazers_count: 2080; archived: false; fork: false.
Capability
2 high confidenceOne attribute. The multi-instrument credit was withdrawn on re-verification: the attribute asks what the model ACCEPTS, and AlphaGenome accepts DNA sequence - the diversity is in its assay outputs. That is the same distinction that excludes GEDI from granite-geospatial, where lidar is a label source rather than an input. The resolution span stands, and a broad prediction surface is not model adaptation.
- https://raw.githubusercontent.com/google-deepmind/alphagenome/main/README.md recorded 2026-09-10
Documents gene-expression, splicing, chromatin, and contact-map output modalities over sequences up to one million bases, mostly at single-base resolution.
Verified 2026-09-10