aid: evolutionaryscale
url: https://raw.githubusercontent.com/api-evangelist/evolutionaryscale/refs/heads/main/apis.yml
apis:
- aid: evolutionaryscale:forge-esm3-api
  name: EvolutionaryScale Forge ESM3 API
  tags:
  - AI
  - Biology
  - Foundation Models
  - Proteins
  - ESM3
  - Generation
  humanURL: https://forge.evolutionaryscale.ai
  properties:
  - url: https://forge.evolutionaryscale.ai
    type: Documentation
  - url: https://github.com/Biohub/esm
    type: SourceCode
  - url: openapi/evolutionaryscale-forge-esm3-api-openapi.yml
    type: OpenAPI
  - url: json-schema/evolutionaryscale-esm-protein-schema.json
    type: JSONSchema
  - url: json-schema/evolutionaryscale-generation-config-schema.json
    type: JSONSchema
  - url: json-ld/evolutionaryscale-context.jsonld
    type: JSONLD
  - type: NaftikoCapability
    url: capabilities/forge-esm3-generation.yaml
  - type: NaftikoCapability
    url: capabilities/forge-esm3-encoding.yaml
  description: Hosted inference API for the ESM3 multimodal protein language model. Reasons jointly across
    sequence, structure, and function tracks. Provides generate, batch_generate, encode, decode,
    forward_and_sample, and logits operations across small (1.4B), medium (7B), and large (98B) parameter
    checkpoints. Accessed via the `esm` Python SDK (`pip install esm`) using a bearer token issued by
    forge.evolutionaryscale.ai. Closed beta with commercial license tiers.
- aid: evolutionaryscale:forge-esmc-api
  name: EvolutionaryScale Forge ESM Cambrian API
  tags:
  - AI
  - Biology
  - Foundation Models
  - Proteins
  - ESM Cambrian
  - Embeddings
  - Representation Learning
  humanURL: https://forge.evolutionaryscale.ai
  properties:
  - url: https://forge.evolutionaryscale.ai
    type: Documentation
  - url: https://github.com/Biohub/esm
    type: SourceCode
  - url: openapi/evolutionaryscale-forge-esmc-api-openapi.yml
    type: OpenAPI
  - url: json-schema/evolutionaryscale-logits-output-schema.json
    type: JSONSchema
  - type: NaftikoCapability
    url: capabilities/forge-esmc-embeddings.yaml
  description: Hosted inference API for the ESM Cambrian (ESM C) protein representation learning model family.
    Drop-in replacement for ESM2 offering comparable accuracy at lower memory footprint. Available in 300M,
    600M, and 6B parameter sizes. Exposes encode and logits operations for generating protein sequence
    embeddings, hidden states, and per-residue logits for downstream representation tasks.
- aid: evolutionaryscale:forge-folding-api
  name: EvolutionaryScale Forge Folding API
  tags:
  - AI
  - Biology
  - Foundation Models
  - Proteins
  - Structure Prediction
  - Inverse Folding
  humanURL: https://forge.evolutionaryscale.ai
  properties:
  - url: https://forge.evolutionaryscale.ai
    type: Documentation
  - url: https://github.com/Biohub/esm
    type: SourceCode
  - url: openapi/evolutionaryscale-forge-folding-api-openapi.yml
    type: OpenAPI
  - type: NaftikoCapability
    url: capabilities/forge-folding-structure.yaml
  description: Hosted folding and inverse-folding inference endpoints. `fold` predicts protein backbone
    coordinates plus pLDDT/PTM confidence from an input sequence; `inverse_fold` designs candidate sequences
    consistent with an input structure. Includes an `msa` endpoint for fetching multiple sequence alignments
    used to condition predictions.
- aid: evolutionaryscale:esm-python-sdk
  name: EvolutionaryScale ESM Python SDK
  tags:
  - AI
  - Biology
  - SDK
  - Python
  - Open Source
  - ESM3
  - ESM Cambrian
  humanURL: https://github.com/Biohub/esm
  properties:
  - url: https://github.com/Biohub/esm
    type: SourceCode
  - url: https://pypi.org/project/esm/
    type: SDK
  - url: https://huggingface.co/biohub/esm3-sm-open-v1
    type: Documentation
  - url: https://huggingface.co/biohub/esmc-300m-2024-12
    type: Documentation
  - url: https://huggingface.co/biohub/esmc-600m-2024-12
    type: Documentation
  - url: https://github.com/Biohub/esm/tree/main/cookbook
    type: CodeExamples
  description: Official Python SDK packaging ESM3 and ESM Cambrian model loaders, the `ESMProtein`
    multi-track data model, generation/sampling configurations, structure tokenization utilities, and a
    `forge.client()` factory that swaps local checkpoints for Forge-hosted inference without code changes.
    Installable from PyPI as `esm`. Mixed commercial / non-commercial licenses.
name: EvolutionaryScale
tags:
- AI
- Artificial Intelligence
- Biology
- Bioinformatics
- Computational Biology
- Drug Discovery
- ESM
- ESM3
- ESM Cambrian
- Foundation Models
- Generative Biology
- Life Sciences
- Machine Learning
- Protein Design
- Protein Folding
- Protein Language Models
- Proteins
- Representation Learning
- Structure Prediction
commonProperties:
- url: https://www.evolutionaryscale.ai
  type: Portal
- url: https://forge.evolutionaryscale.ai
  name: EvolutionaryScale Forge
  type: SignUp
- url: https://github.com/Biohub/esm
  name: ESM SDK on GitHub
  type: SourceCode
- url: https://pypi.org/project/esm/
  name: esm package on PyPI
  type: SDK
- url: https://huggingface.co/biohub
  name: Biohub on Hugging Face
  type: Documentation
- url: https://huggingface.co/biohub/esm3-sm-open-v1
  name: ESM3-open (1.4B) on Hugging Face
  type: Models
- url: https://huggingface.co/biohub/esmc-300m-2024-12
  name: ESM C 300M on Hugging Face
  type: Models
- url: https://huggingface.co/biohub/esmc-600m-2024-12
  name: ESM C 600M on Hugging Face
  type: Models
- url: https://github.com/Biohub/esm/tree/main/cookbook
  name: ESM Cookbook
  type: CodeExamples
- url: https://github.com/Biohub/esm/tree/main/cookbook/tutorials
  name: ESM Tutorials
  type: Tutorials
- url: https://www.science.org/doi/10.1126/science.ads0018
  name: ESM3 — Science paper (Hayes et al. 2025)
  type: Documentation
- url: https://www.evolutionaryscale.ai/blog/esm3-release
  name: ESM3 release announcement
  type: Blog
- url: https://www.evolutionaryscale.ai/blog/esm-cambrian
  name: ESM Cambrian announcement
  type: Blog
- url: https://www.evolutionaryscale.ai/blog
  type: Blog
- url: https://aws.amazon.com/marketplace/seller-profile?id=seller-iw2nbscescndm
  name: EvolutionaryScale on AWS Marketplace (SageMaker)
  type: Marketplace
- url: https://github.com/evolutionaryscale/esm-sagemaker
  name: ESM on Amazon SageMaker examples
  type: CodeExamples
- url: https://github.com/evolutionaryscale/esm-partner
  name: Partner integrations
  type: CodeExamples
- url: https://www.evolutionaryscale.ai/policies/cambrian-inference-clickthrough-license-agreement
  name: Cambrian Inference Clickthrough License Agreement
  type: TermsOfService
- url: https://responsiblebiodesign.ai
  name: Responsible Biodesign Framework
  type: Documentation
- url: https://bit.ly/esm-slack
  name: ESM Community Slack
  type: Forum
- url: https://github.com/evolutionaryscale
  type: GitHubOrganization
- url: https://github.com/Biohub
  name: Biohub GitHub Organization (ESM home)
  type: GitHubOrganization
- url: plans/evolutionaryscale-plans-pricing.yml
  type: Plans
- url: rate-limits/evolutionaryscale-rate-limits.yml
  type: RateLimits
- url: finops/evolutionaryscale-finops.yml
  type: FinOps
- url: vocabulary/evolutionaryscale-vocabulary.yml
  type: Vocabulary
- type: Models
  data:
  - name: esm3-large-2024-03
    parameters: 98B
    description: Largest ESM3 checkpoint, trained on 771B tokens from 2.78B natural proteins; 1e24 FLOPs.
  - name: esm3-medium-2024-08
    parameters: 7B
    description: Mid-size ESM3 checkpoint suitable for most Forge inference workloads.
  - name: esm3-small-2024-08
    parameters: 1.4B
    description: Small ESM3 checkpoint; open weights as esm3-sm-open-v1 (non-commercial use).
  - name: esm3-open
    parameters: 1.4B
    description: Open weights of esm3-small (biohub/esm3-sm-open-v1 on Hugging Face).
  - name: esmc-6b-2024-12
    parameters: 6B
    description: Largest ESM Cambrian representation model.
  - name: esmc-600m-2024-12
    parameters: 600M
    description: Mid-size ESM Cambrian representation model.
  - name: esmc-300m-2024-12
    parameters: 300M
    description: Small ESM Cambrian model; ESM2 650M-class quality with reduced memory footprint.
- type: Features
  data:
  - ESM3 — multimodal generative model jointly conditioning on protein sequence, structure, and function
  - 98B-parameter ESM3 trained on 771B tokens from 2.78B natural proteins (1e24 FLOPs)
  - ESM Cambrian (ESM C) representation models at 300M, 600M, and 6B parameters
  - Forge API providing generate, batch_generate, encode, decode, forward_and_sample, and logits operations
  - Fold and inverse-fold endpoints for structure prediction and structure-conditioned sequence design
  - MSA endpoint for fetching multiple sequence alignments used by structure prediction
  - Iterative masked sampling with configurable num_steps, temperature, top_p, and decoding schedules
  - Per-track generation across sequence, structure, secondary_structure, sasa, and function tracks
  - Structure tokenizer converting PDB / atom37 coordinates to and from discrete tokens
  - ESMProtein and ESMProteinTensor data model unifying raw and tokenized representations
  - Async/sync client surface (`async_generate`, `async_fold`, `async_encode`, ...) for high-throughput jobs
  - Drop-in Forge client (`esm.sdk.client(model, token=...)`) replaces local checkpoints with hosted inference
  - Open-weights ESM3-open (1.4B) and ESM Cambrian distributions on Hugging Face under research license
  - AWS Marketplace deployment via SageMaker, NVIDIA BioNeMo, and NVIDIA NIM microservice
  - Cookbook tutorials covering protein generation, embedding workflows, and esmGFP-style design
  - Responsible Biodesign Framework governing model release and biosecurity review
  sources:
  - https://www.evolutionaryscale.ai
  - https://github.com/Biohub/esm
  - https://forge.evolutionaryscale.ai
  - https://www.science.org/doi/10.1126/science.ads0018
  - https://www.evolutionaryscale.ai/blog/esm3-release
  - https://www.evolutionaryscale.ai/blog/esm-cambrian
  updated: '2026-05-24'
created: '2026-05-24'
modified: '2026-05-24'
position: Consuming
description: EvolutionaryScale is a New York-based biology foundation model lab spun out of Meta AI's
  ESM team that develops AI to deepen scientific understanding of biology. Its flagship ESM3 model is a
  multimodal generative protein language model that reasons jointly across sequence, structure, and
  function, scaling to 98B parameters trained on 771B tokens from 2.78B natural proteins. The companion
  ESM Cambrian (ESM C) family provides protein representation learning at 300M–6B parameters as a
  performant ESM2 replacement. Models are accessible via the hosted Forge inference API
  (forge.evolutionaryscale.ai), an open-source Python SDK (`pip install esm`), open weights on Hugging
  Face, and AWS Marketplace (SageMaker, NVIDIA BioNeMo and NIM). EvolutionaryScale was integrated into
  the Biohub organization in 2025; the ESM SDK now lives at github.com/Biohub/esm.
maintainers:
- FN: Kin Lane
  email: info@apievangelist.com
  X: apievangelist
  url: https://apievangelist.com
specificationVersion: '0.16'