Evo 2
A Historic Breakthrough in Genomic AI
Developed through a groundbreaking collaboration between Arc Institute, Stanford University, NVIDIA, UC Berkeley, and leading researchers, Evo 2 represents a monumental advancement in AI-driven genomics. This powerful new model is poised to redefine biological research, precision medicine, and synthetic biology.
evo2 page NVIDIA¹
Trained on an unprecedented 9.3 trillion DNA base pairs, Evo 2 pushes the boundaries of artificial intelligence in genomics, making it possible to predict, model, and even design biological systems across all domains of life.
Why Evo 2 is a Game-Changer
- 7B & 40B parameters
- 1M-token context window
- Single-nucleotide resolution
- Extraordinary accuracy in identifying functional impacts of genetic mutations
- First-of-its-kind AI that synthesizes mitochondrial, prokaryotic & eukaryotic genomes
- Autonomously learns exon-intron boundaries, transcription factor sites & protein structures
- The entire model, training code & OpenGenome2 dataset are freely available for researchers
Evo 2 Technical Specifications
Evo 2 is a biological foundation model with 40 billion parameters, making it the largest AI model for biology to date. It integrates information over long genomic sequences while maintaining sensitivity to single-nucleotide changes. The model understands the genetic code for all domains of life and was trained on nearly 9 trillion nucleotides.
Architecture Details
- Architecture Type: Generative Neural Network
- Network Architecture: StripedHyena
- Input: DNA Sequences (with optional taxonomy prompts)
- Output: DNA Sequences
Evo 2 operates across all domains of life, processing genomic data at single-nucleotide resolution while maintaining context across long sequences.
Capabilities
- Zero-shot function prediction for genes
- Multi-element generation tasks, such as generating synthetic CRISPR-Cas molecular complexes
- Prediction of gene essentiality at nucleotide resolution
- Generation of coding-rich sequences up to at least 1M kb in length
The Future of AI-Driven Biology is Here
Released on February 19, 2025, Evo 2 is commercially ready and globally available. Built on PyTorch and Transformer Engine, it’s optimized for NVIDIA Hopper architecture and can run on H200 and H100 GPUs.
As advancements in multi-modal and multi-scale learning continue with Evo, we’re witnessing a promising path toward improving our understanding and control of biology across multiple levels of complexity.
How do you see Evo 2 shaping the next medical and biotechnological breakthroughs?
References
¹ “EVO:2-40B.” NVIDIA. https://build.nvidia.com/arc/evo2-40b/modelcard