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Evo 2 40B
Container
arc
Evo 2 40B

Evo 2 is a biological foundation model that is able to integrate information over long genomic sequences.

  • BioNeMo Evo 2 40B NIM Overview

    Description:

    Evo 2 is a biological foundation model that integrates information across long genomic sequences while retaining sensitivity to single-nucleotide changes. At 40 billion parameters, the model understands the genetic code for all domains of life and is the largest AI model for biology to date. Evo 2 was trained on a dataset of nearly 9 trillion nucleotides.

    The container components are ready for commercial or non-commercial use.

    Third-Party Community Consideration

    This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case. The container includes the third-party Evo 2 40B model (arcinstitute/evo2_40b).

    License / Terms of Use

    GOVERNING DOWNLOAD TERMS: Use of this container is governed by the NVIDIA Software License Agreement and Product-Specific Terms for AI Products. Use of the model is governed by the NVIDIA Open Model License Agreement. ADDITIONAL INFORMATION: Apache 2.0 License.

    You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.

    Deployment Geography

    Global

    Use Case

    Evo is able to perform zero-shot function prediction for genes. Evo also can perform multi-element generation tasks, such as generating synthetic CRISPR-Cas molecular complexes. Evo 2 can also predict gene essentiality at nucleotide resolution and can generate coding-rich sequences up to at least 1M kb in length. Advances in multi-modal and multi-scale learning with Evo provide a promising path toward improving our understanding and control of biology across multiple levels of complexity.

    Release Date

    NGC: 09/22/2025 via catalog.ngc.nvidia.com
    build.nvidia.com: 09/22/2026 via build.nvidia.com/arc/evo2-40b

    Program Classes:

    The NIM contains the Evo 2 40B model, including Evo 2 inference code and model weights (checkpoint). The model (checkpoint) is pulled automatically at NIM startup.

    Model Name & LinkUse CaseHow to Pull the Model
    Evo 2 40B. Model CardGenerate and analyze DNA sequences across domains of lifeAutomated

    Deployment Details:

    The Evo 2 40B NIM is deployed by pulling and running the container in an environment with appropriate credentials. For instructions to pull and run, hardware requirements, and NVIDIA GPU support matrix, see Evo 2 NIM Docs.

    Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster inference times compared to CPU-only solutions

    References:


    Container Version(s):

    Evo 2 40B v2.2.0

    Security Common Vulnerabilities and Exposures (CVEs)

    Please review the Security Scanning tab on NGC to view the latest security scan results. For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

    Ethical Considerations:

    NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. Developers should work with their internal developer team to ensure these software components meet requirements for the relevant industry and use case and address unforeseen product misuse.

    Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

    Get Help

    Getting started with the NIM

    Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container page for release documentation, deployment guides and more Evo 2 NIM Docs.

    Enterprise Support

    Get access to knowledge base articles and support cases or submit a ticket.

    Publisher
    arc
    Latest Tag2.2
    UpdatedSeptember 22, 2026 UTC
    Compressed Size14.19 GB
    Multinode SupportNo
    Multi-Arch SupportNo

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