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Compare biological models, docking engines, and computational workflows side-by-side. Filter by access model, compute footprint, and category to reach an actionable decision table in under a minute.
| Attribute | ＋ Add tool | |
|---|---|---|
| Category | Biological Foundation Models | — |
| Subcategory | Protein Language Models | — |
| Company | Salesforce AI Research | — |
| Access mode | Open Source | — |
| Licence conditions | BSD-3-Clause | — |
| Compute requirements | 1x GPU (>= 16GB VRAM) for inference | — |
| Biological application | Enzyme engineering, antibody optimization, and zero-shot fitness prediction | — |
| Research workflow | Generate sequence variants with high predicted stability and activity | — |
| Evidence level | Peer-reviewed publication (NeurIPS 2023) | — |
| Commercial eligibility | Permissive open source release | — |
| Price | Free Open Source | — |
| Availability ⓘ | Available on GitHub and Hugging Face | — |
| Features | Trained on over 1 billion sequences from UniParc, BFD, and metagenomic sources, Controllable sequence generation with tag-based conditioning, High accuracy zero-shot variant effect prediction, Model sizes ranging from 150M to 6.4B parameters | — |
| Entry type | AI Model | — |
| AI role | Generative Protein Modeling | — |
| Input data | Not recorded | — |
| Output data | Not recorded | — |
| Validation | Not recorded | — |
| Type | Autoregressive protein language model | — |
| Intended use | Not recorded | — |
| Compatibility | Not recorded | — |
| Manufacturer | Salesforce AI Research | — |
| Integration evidence | https://github.com/salesforce/progen | — |
| Laboratory handoff | Sequences ready for oligonucleotide synthesis and screening | — |