ESM-3

weights

open(ungated esm3_sm_open_v1.pth with structure and function decoder weights alongside)

data

closed(2.78 billion natural proteins described by count, corpus not released)

code

partial(inference, generation and tutorial code in the esm package

license

MIT(OSI

The checkpoint's Hugging Face namespace moved to biohub with no license field on the destination card, but MIT is still stated in the card body and in the repository's LICENSE.md, so the grant survives even though it is asserted in prose rather than declared as metadata. Only the 1.4B checkpoint is downloadable; the 7B and 98B models remain available only through the hosted API.

• https://huggingface.co/api/models/EvolutionaryScale/esm3-sm-open-v1 recorded 2026-09-10

  Redirects to huggingface.co/api/models/biohub/esm3-sm-open-v1; gated: false; private: false; no license tag and no cardData license key; data/weights/esm3_sm_open_v1.pth, esm3_structure_decoder_v0.pth and esm3_function_decoder_v0.pth present.

• https://huggingface.co/biohub/esm3-sm-open-v1/raw/main/README.md recorded 2026-09-10

  Front matter declares only language and tags, no license. The body says "This repository is under a MIT license" and links the esm repository LICENSE.md; training is described as 2.78 billion natural proteins, with no corpus released.

• https://raw.githubusercontent.com/Biohub/esm/main/_assets/ESM3_README.md recorded 2026-09-10

  "These models are available under the MIT license." Code covers local inference and generation and a tutorials cookbook; the 7B and 98B tiers are reachable only through the hosted platform.

• https://raw.githubusercontent.com/Biohub/esm/main/LICENSE.md recorded 2026-09-10

  "License (MIT)", Copyright 2026 Chan Zuckerberg Biohub, Inc., with the standard MIT permission grant.

Adoption is measured as trailing-30-day Hugging Face downloads of biohub/esm3-sm-open-v1, the one openly distributed checkpoint. The larger 7B and 98B tiers are served only through the hosted Forge API, which publishes no artifact count, so they sit outside the counted scope rather than being folded into it.

• https://huggingface.co/api/models/biohub/esm3-sm-open-v1 recorded 2026-09-10

  downloads: 2772; likes: 330.

Two attributes are read directly off the publisher's description: three joint sequence, structure and function tracks, and generation from a partial prompt. Adaptation is not credited, because the release documents how to prompt and sample rather than how to fine-tune, and the repository's fine-tuning guidance targets ESMC rather than ESM-3.

• https://huggingface.co/biohub/esm3-sm-open-v1/raw/main/README.md recorded 2026-09-10

  "a generative model capable of designing proteins conditioned on partial prompts of sequence, structure and function"; usage points to the esm repository notebooks, with no fine-tuning entry point.

• https://raw.githubusercontent.com/Biohub/esm/main/_assets/ESM3_README.md recorded 2026-09-10

  "able to jointly reason across three fundamental biological properties of proteins: sequence, structure, and function ... represented as tracks of discrete tokens at the input and output"; "ESM3 is a generative masked language model. You can prompt it with partial sequence, structure, and function keywords, and iteratively sample masked positions".