Evo, a long-context biological foundation model, has been developed using the StripedHyena architecture, which generalizes across DNA, RNA, and proteins. The model is capable of predicting tasks and generating designs at both molecular and genome scales, with an unprecedented level of sensitivity to single-nucleotide changes. Evo's capabilities include zero-shot gene essentiality testing, zero-shot prediction across DNA, RNA, and protein modalities, CRISPR system generation, and genome-scale generation. The model has been trained on a large corpus of prokaryotic genomic sequences covering 2.7 million whole genomes and is available for use via the Together API and Playground. Evo has the potential to accelerate biological discovery and understanding, as well as be applied to real-world problems such as drug discovery, agriculture, and sustainability. However, further experimental validation is required for the generated sequences.