AlphaFold 2 vs ColabFold
AlphaFold 2: DeepMind's open-source protein structure prediction model (monomer and multimer). ColabFold: Fast, accessible protein folding with MMseqs2 + AlphaFold in Colab.
Facts below come from each project's own website, repository and paper. We don't publish benchmark claims here; see the papers for evaluations. Shared tags: structure.
| Field | AlphaFold 2 | ColabFold |
|---|---|---|
| Task | Structure prediction | Structure prediction |
| Modalities | Monomer, multimer | Monomer, complex |
| MSA required | Yes (genetic databases) | Yes (MMseqs2 server) |
| Open weights | — | — |
| GPU need | NVIDIA GPU | One GPU ≈ 1,000 structures/day |
| License | Apache-2.0 | MIT |
| Pricing | Open source | Open source |
| Released | 2021-07-15 | 2021-07-22 |
| Paper | Link | Link |
| GitHub | GitHub | GitHub |
| GitHub stars | 14,890 | 2,964 |
| Interface | Docker, Colab | Package, Docker, Colab, Web |
License and commercial use
| Field | AlphaFold 2 | ColabFold |
|---|---|---|
| Code license | Apache-2.0 | MIT |
| Weights license | — | — |
| Commercial use | Permissive (commercial OK) | Permissive (commercial OK) |
| Answer | Yes. The recorded license is permissive, so closed-source commercial use is allowed if you keep the notices. Details | Yes. The recorded license is permissive, so closed-source commercial use is allowed if you keep the notices. Details |
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