What it is
Chai Discovery introduces Chai-1, a multi-modal foundation model designed for molecular structure prediction, achieving state-of-the-art performance in drug discovery tasks. The model supports a wide array of predictions including proteins, small molecules, and nucleic acids,…
Gabriel’s notes
Chai-1 is a new multi-modal foundation model for molecular structure prediction that performs at the state-of-the-art across a variety of tasks relevant to drug discovery. Chai-1 enables unified prediction of proteins, small molecules, DNA, RNA, covalent modifications, and more. Available for free via a web interface, including for commercial applications such as drug discovery. Also releasing the model weights and inference code as a software library for non-commercial use.
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Pricing snapshot (auto-enriched): Free tier available via web interface for commercial use; open-source software library under Apache 2.0 License; no mention of usage-based or per seat pricing or hidden limits.
Work-use / compliance snapshot (auto-enriched): The Chai-1 model from Chai Discovery is available for commercial use and released under an Apache 2.0 License, but there is no publicly available information on data handling, training usage, retention, SSO availability, or compliance certifications such as SOC2, HIPAA, or GDPR.
Alternatives (auto-enriched): Alternative: AlphaFold | Comparison: AlphaFold is a leading protein structure prediction tool, but Chai-1 offers multi-modal capabilities and can predict multimer structures using single sequences without MSAs, providing comparable or better performance in some benchmarks.
Reading tip: skim headings first, then focus on the sections that match your current project or question.
Note: pricing and policy details can change—verify on the official site before making decisions.