{"entity":{"id":"cellfm","kind":"technology","name":"CellFM","aka":[],"tldr":"CellFM is an 800-million-parameter single-cell model trained on 100 million human cells.","summary":"CellFM is a single-cell foundation model from a Chinese consortium, a transformer with efficient attention over gene tokens that scales to 800 million parameters, among the largest single-cell models by parameter count. The 2024 bioRxiv preprint trained it on 100 million human cells and reported gains on cell-type annotation and perturbation prediction tasks. It is a research model for computational biologists exploring whether scale alone improves single-cell prediction. Independent evaluation is limited, and the wider field has found that many single-cell foundation models barely beat simple baselines on perturbation tasks, so its reported gains need external replication. For a newcomer: CellFM is one of the biggest models of its kind, but outsiders have not yet confirmed how much the extra size helps.","status":"emerging","asOf":"2026-09-08","links":[{"label":"bioRxiv 2024","url":"https://www.biorxiv.org/content/10.1101/2024.06.04.597369v1"}],"tags":["foundation-model","virtual-cell"],"related":["scfoundation"],"cancers":[],"sections":["ai-computation"],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":[],"trials":[],"people":[],"bottlenecks":[],"keyPapers":[],"journals":[],"dependsOn":[],"notes":[],"principle":"CellFM is a transformer with efficient attention over gene tokens.","strengths":["Scale"],"limitations":["Limited independent evaluation"],"since":2024},"route":"/technologies/cellfm/","neighbours":{"technology":[{"id":"scfoundation","kind":"technology","name":"scFoundation (BioMap)","route":"/technologies/scfoundation/"}],"section":[{"id":"ai-computation","kind":"section","name":"AI & Computation","route":"/fronts/ai-computation/"}]}}