Evo 2Arc Institute
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TimestralMistral AI
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About
Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework.
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About
Timestral is a family of time-series foundation models and a Python inference package for generating multivariate probabilistic forecasts from historical sequences. The four model sizes (5M, 28M, 123M and 209M parameters) support past-only, known-future and categorical covariates, return quantile forecasts, and accept context windows up to 32,768 time steps. Developers can load pretrained weights from the Hugging Face Hub or from local files and run inference on CPU or GPU, then incorporate forecasts into monitoring, capacity-planning, energy, supply-chain, financial-risk, or maintenance workflows. Timestral supports zero-shot forecasting and can be adapted to domain data through Mistral Forge. The package is intended for data scientists, machine-learning engineers, and teams building forecasting systems; repository code is Apache 2.0, while model weights use a separate Modified MIT license.
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Platforms Supported
Windows
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Mac
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Linux
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Cloud
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On-Premises
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iPhone
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Chromebook
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Not Supported
On-Premises
Supported
iPhone
Not Supported
iPad
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Android
Not Supported
Chromebook
Not Supported
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Audience
Computational biologists and genetic engineers in need of a tool to model and design biological sequences across multiple modalities, enhancing research in genomics and synthetic biology
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Audience
Data scientists, machine-learning engineers, forecasting practitioners, and teams developing time-series forecasting systems.
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Support
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24/7 Live Support
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Online
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Support
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API
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API
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Pricing
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Free Version
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Pricing
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Reviews/
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Training
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Live Online
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Training
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Company InformationArc Institute
United States
arcinstitute.org/tools/evo
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Company InformationMistral AI
Founded: 2023
France
github.com/mistralai/timestral
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Integrations
Evo Designer
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GitHub
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Hugging Face
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Mistral Forge
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NVIDIA BioNeMo
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Integrations
Evo Designer
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GitHub
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Hugging Face
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Mistral Forge
Supported
NVIDIA BioNeMo
Not Supported
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