Evo 2 and the Rise of Long Context Genomics

Evo 2 and the Rise of Long Context Genomics One of the most technically important biology and AI stories of the past two weeks is the formal publication of Evo 2 in Nature on March 4, 2026. The model is not just another biological language model with a larger parameter count. What makes it significant is the combination of scale, context length, and task breadth. According to the paper, Evo 2 was trained on 9 trillion DNA base pairs from a curated atlas spanning all domains of life, and it operates with a 1 million token context window at single nucleotide resolution. That is a very different regime from earlier sequence models that were forced to reason over much shorter windows and therefore struggled to capture regulatory interactions spread across large genomic distances. ( Nature ) The technical implication is easy to underestimate. In genomics, local sequence motifs matter, but many of the hardest problems are not purely local. Enhancers can act at long range. Noncoding variants