EvolutionaryScale website screenshot

EvolutionaryScale

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.

4 APIs 0 Features
AIArtificial IntelligenceBiologyBioinformaticsComputational BiologyDrug DiscoveryESMESM3ESM CambrianFoundation ModelsGenerative BiologyLife SciencesMachine LearningProtein DesignProtein FoldingProtein Language ModelsProteinsRepresentation LearningStructure Prediction

APIs

EvolutionaryScale Forge ESM3 API

Hosted inference API for the ESM3 multimodal protein language model. Reasons jointly across sequence, structure, and function tracks. Provides generate, batch_generate, encode, ...

EvolutionaryScale Forge ESM Cambrian API

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 footpri...

EvolutionaryScale Forge Folding API

Hosted folding and inverse-folding inference endpoints. `fold` predicts protein backbone coordinates plus pLDDT/PTM confidence from an input sequence; `inverse_fold` designs can...

EvolutionaryScale ESM Python SDK

Official Python SDK packaging ESM3 and ESM Cambrian model loaders, the `ESMProtein` multi-track data model, generation/sampling configurations, structure tokenization utilities,...

Collections

EvolutionaryScale Forge ESM3 API

OPEN

EvolutionaryScale Forge ESM Cambrian API

OPEN

EvolutionaryScale Forge Folding API

OPEN

Pricing Plans

Evolutionaryscale Plans Pricing

4 plans

PLANS

Rate Limits

Evolutionaryscale Rate Limits

7 limits

RATE LIMITS

FinOps

Evolutionaryscale Finops

FINOPS

Semantic Vocabularies

Evolutionaryscale Context

0 classes · 5 properties

JSON-LD

API Governance Rules

EvolutionaryScale API Rules

7 rules · 3 errors 4 warnings

SPECTRAL

Example Payloads

Evolutionaryscale Forge Esmc Logits Example

2 fields

EXAMPLE

Evolutionaryscale Forge Fold Example

2 fields

EXAMPLE

Evolutionaryscale Forge Generate Example

2 fields

EXAMPLE

Sources

Raw ↑ 
opencollection: 1.0.0
info:
  name: EvolutionaryScale Forge Folding API
  version: Wed Jul 31 2024 20:00:00 GMT-0400 (Eastern Daylight Time)
request:
  auth:
    type: bearer
    token: '{{bearerToken}}'
items:
- info:
    name: Structure
    type: folder
  items:
  - info:
      name: Fold Sequence To Structure
      type: http
    http:
      method: POST
      url: https://forge.evolutionaryscale.ai/api/v1/fold
      body:
        type: json
        data: '{}'
    docs: 'Predict atom37 backbone coordinates, per-residue pLDDT confidence, and predicted TM-score (PTM) for an input amino
      acid sequence. Returns a full `ESMProtein` with `coordinates`, `plddt`, and `ptm` populated.

      '
  - info:
      name: Inverse Fold Structure To Sequence
      type: http
    http:
      method: POST
      url: https://forge.evolutionaryscale.ai/api/v1/inverse_fold
      body:
        type: json
        data: '{}'
    docs: 'Generate one or more candidate amino acid sequences that fold to the provided structure. Accepts atom37 coordinates
      plus optional per-residue temperature controls.

      '
- info:
    name: MSA
    type: folder
  items:
  - info:
      name: Fetch Multiple Sequence Alignment
      type: http
    http:
      method: POST
      url: https://forge.evolutionaryscale.ai/api/v1/msa
      body:
        type: json
        data: '{}'
    docs: 'Fetch a multiple sequence alignment (MSA) for the input sequence. The MSA can be passed into subsequent fold calls
      to improve accuracy.

      '
bundled: true