ESMFold

Single-sequence structure prediction with no MSA required.

Developer: Meta AI (FAIR) Evolutionary Scale Modeling

Commercial use OKFree for commercial use

Overview

Developer
Meta AI (FAIR) Evolutionary Scale Modeling
Commercial rights
Commercial OK
Commercial cost
Free commercially
Compute
Single GPU
Open weights
Yes
Last verified

Capabilities

MSA-free structure prediction. Input: a single protein sequence; output: an all-atom PDB with pLDDT in seconds-to-minutes, no MSA search needed. Good for screening thousands of designed sequences; weaker than AlphaFold2 on natural targets.

When to use it

Use when you need fast structures for thousands of sequences without MSAs, e.g. filtering design libraries. Less accurate than AF2/Boltz on hard targets and not a complex predictor.

Input / Output

Input
a single protein sequence
Output
an all-atom PDB with pLDDT in seconds-to-minutes, no MSA search needed

Compute

Single GPU. Other tools with this compute profile →

Commercial Licensing

Commercial rights — may a company use it?

Commercial use OK

Licence as writtenMIT License

MIT LICENSE file in the facebookresearch/esm repo covering the released code and models.

The licence read at the source allows use by a company. Attribution or copyleft conditions may still apply — read the note.

Commercial cost — is commercial use free of charge?

Free for commercial use

Nothing to pay: the licence read at the source grants commercial use with no fee, and the code and weights are public downloads. You still pay for your own compute.

Original sources — read on 15 Oct 2026
  1. raw.githubusercontent.com/facebookresearch/esm/main/LICENSE

Price and rights are separate: this panel is about money, the panel above is about permission.

  • Commercial OK ≠ Free of charge. A tool can be licensed for company use and still need a paid licence for a dependency (BindCraft → PyRosetta).
  • Free download ≠ Commercially licensed. Weights you can download at no cost may still forbid commercial use (AlphaFold 3).
  • Unverified ≠ Commercially permitted. If no published statement settles it, treat it as unknown — not as a yes.
  • Every component counts. Each status considers the code licence, the model-weights terms, required dependencies and any terms of use.

Model Weights

Open weights. A separate weights licence is Not documented as its own field; where weights carry different terms from the code, that is stated in the licence explanation above.

Dependencies

Not documented as a separate field. Any dependency that affects commercial use (for example a paid PyRosetta licence) is named in the licence and cost explanations above.

Official References

From the makers of FoldScout

From AI Design to Wet-Lab Validation

Designed a promising protein or antibody? Seq2Study helps translate AI-generated sequences into experimental data.

  • Protein Expression
  • Protein Purification
  • Binding Affinity
  • Aggregation Assessment
  • Stability Evaluation
  • Developability Assessment
Explore Seq2Study