Architecture comparison

EvolutionaryScale vs Ginkgo Bioworks

EvolutionaryScale runs closer to the foundational model (Native (own / self-hosted weights)) than Ginkgo Bioworks (Native (own / self-hosted weights)). Shared foundation: proprietary / self-built models (highlighted).

EvolutionaryScale

Biotech

Proximity

Native (own / self-hosted weights)

Models

proprietary / self-built models

Cloud · datastore

AWSobject storage (S3 or equivalent, inferred)domain-specific biological data stores (inferred)

Compliance

—

Architecture

EvolutionaryScale operates ESM3 as a proprietary, GPU-accelerated protein LLM stack on AWS, exposing commercial access primarily via AWS SageMaker, AWS HealthOmics, and soon Amazon Bedrock, while distributing a smaller open version of ESM3 and earlier ESM models with code and some weights on GitHub and Hugging Face for non-commercial and open use.[3][5][7][11] Internal architecture details beyond this cloud/HPC and PyTorch-centric GPU cluster setup are not publicly documented.[3][10][12]

Ginkgo Bioworks

Biotech

Proximity

Native (own / self-hosted weights)

Models

proprietary / self-built models

Cloud · datastore

AWSown

Compliance

SOC 2

Architecture

Cell-programming foundry training its own biological/sequence models over massive lab data.

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