BaseFold
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
- Basecamp Research
- Organisation type
- Industry
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 6 March 2024
- Authors
- Geraldene Munsamy, Tanggis Bohnuud, Philipp Lorenz
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein folding prediction
- Base model
- AlphaFold 2
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
Number of Sequences (1 x 10⁹) × Average Residues per Sequence (300) = 3 × 10¹¹ datapoints Final estimate: 3 × 10¹¹
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA A100
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
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
- IMPROVING ALPHAFOLD2 PERFORMANCE WITH A GLOBAL METAGENOMIC & BIOLOGICAL DATA SUPPLY CHAIN
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
BaseFold was published by Basecamp Research, in the country recorded as United Kingdom of Great Britain and Northern Ireland, during March 2024. The category the publisher falls under is industry.
It works in the domain of Biology, and is recorded as performing the task of protein folding prediction.
Its starting point was an existing base model, AlphaFold 2. Most models at this scale are adapted from an existing base rather than built from nothing.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
BaseFold — common questions
BaseFold— when was it released?
It was published in March 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.
BaseFold— what is it used for?
It works in the domain of Biology, and is recorded as handling the task of protein folding prediction. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
BaseFold— what GPU do I need to run it?
None. This 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.
BaseFold— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
BaseFold— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
BaseFold— who created it?
It was published by Basecamp Research, based in United Kingdom of Great Britain and Northern Ireland, an organisation categorised as industry.
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.