Cryofm V 2 is a flow-based generative foundation model for cryo-EM density maps developed by ByteDance, exceling at learning general priors of high-quality cryo-EM densities and adaptable for downstream tasks such as density map enhancement. Its 3D UNet architecture enables stable generation and flexible adaptation, with a notable technical trait being its use of positional encoding for time embedding.
Input
Output
Context
-
Max Output
-
Parameters
-
Input Modalities
Output Modalities
Data sourced from official provider APIs and documentation
Last updated: Jun 23, 2026
Automatically route workloads to the right model for every task, every time.