ByteDanceCryofm V1
ByteDance's Cryofm V 1 is a flow-based foundation model for 3D cryo-electron microscopy density maps, employing a Hierarchical Diffusion Transformer architecture to learn deep priors of 3D cryo-EM densities. It is genuinely best at supporting various downstream tasks including density map denoising, anisotropy noise correction, and missing wedge inpainting.
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Frequently asked questions about Cryofm V1
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
ByteDance has not published a context window for Cryofm V1, so the catalog shows it as not available rather than estimating one.
Yes. Cryofm V1 is an open-weight model released under the Apache 2.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Cryofm V1 accepts Image and produces Image. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Cryofm V1 is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Cryofm V1 is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
ByteDance has not published a parameter count for Cryofm V1, so the catalog cannot estimate its memory footprint. The capacity planner can size it from a parameter count you supply.
Fields collected from public registries, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Oct 14, 2026
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