MassiveFold

Closed weights Université de Lille,Linköping University,Universite de Technologie de Compiègne – CNRS November 2024

No estimate

No hardware requirements for this model

The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.

On record

Full specification

Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.

Origin

Who built this model, where, and when it was published.

Organisation
Université de Lille,Linköping University,Universite de Technologie de Compiègne – CNRS
Organisation type
Academia,Academia,Academia
Country
France, Sweden
Published
11 November 2024
Authors
Nessim Raouraoua, Claudio Mirabello, Thibaut Véry, Christophe Blanchet, Bjorn Wallner, Marc Lensink, Guillaume Brysbaert

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Biology
Task
Protein folding prediction

Size

How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.

Training data
tokens

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Record confidence
Unknown

Sources

Where this record came from and when it was last checked.

Reference
MassiveFold: unveiling AlphaFold’s hidden potential with optimized and parallelized massive sampling
Last updated
28 November 2025

What the numbers mean

What this model is

MassiveFold was published by Université de Lille,Linköping University,Universite de Technologie de Compiègne – CNRS, in France, in November 2024. academia,Academia,Academia is the category the publisher falls under.

It works in Biology, and is recorded as doing protein folding prediction.

Its weights were never published, so it can only be reached through its provider. No graphics card changes that.

Answers

MassiveFold — common questions

01

Is MassiveFold open source?

The licensing for MassiveFold was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.

02

How many parameters does MassiveFold have?

No parameter count has been published for MassiveFold, which is why no memory or speed figure appears on this page.

03

Who created MassiveFold?

MassiveFold was published by Université de Lille,Linköping University,Universite de Technologie de Compiègne – CNRS, based in France, categorised as academia,Academia,Academia.

04

When was MassiveFold released?

MassiveFold was published in November 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

05

What is MassiveFold used for?

MassiveFold works in Biology, and is recorded as handling protein folding prediction. These are the areas it was designed around; they describe intent rather than a hard boundary.

06

What GPU do I need to run MassiveFold?

None. MassiveFold is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.

Source

Original publication

Record last updated 28 November 2025

The other direction

Looking at it from the other side?

This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.