Boltz-2
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
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
- Massachusetts Institute of Technology (MIT),Recursion Pharmaceuticals,ETH Zurich,Valence Labs
- Organisation type
- Academia,Industry,Academia,Industry
- Country
- United States of America, Switzerland, Canada
- Published
- 6 June 2025
- Authors
- Saro Passaro, Gabriele Corso, Jeremy Wohlwend, Mateo Reveiz, Stephan Thaler, Vignesh Ram Somnath, Noah Getz, Tally Portnoi, Julien Roy, Hannes Stark, David Kwabi-Addo, Dominique Beaini, Tommi Jaakkola, Regina Barzilay
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein interaction prediction, Protein-ligand binding affinity 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
Wide range of different datasets and data types - I'm unsure how one would go about aggregating these.
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,NVIDIA H100 NVL
- Chips used
- 188
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
- Open — downloadable
- Model access
- Open weights (unrestricted)
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
- Boltz-2: Towards Accurate and Efficient Binding Affinity Prediction
- Last updated
- 28 November 2025
What the numbers mean
Background
Boltz-2 was published by Massachusetts Institute of Technology (MIT),Recursion Pharmaceuticals,ETH Zurich,Valence Labs, in United States of America, in June 2025. It comes out of academia,Industry,Academia,Industry.
It works in Biology, and is recorded as doing protein interaction prediction, Protein-ligand binding affinity prediction.
Because its weights were released, nothing about running it depends on a provider staying available — it is yours once downloaded.
Answers
Boltz-2 — common questions
What GPU do I need to run Boltz-2?
We cannot say. Boltz-2 has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
Is Boltz-2 open source?
Its weights are published, so Boltz-2 can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
How many parameters does Boltz-2 have?
No parameter count has been published for Boltz-2, which is why no memory or speed figure appears on this page.
Who created Boltz-2?
Boltz-2 was published by Massachusetts Institute of Technology (MIT),Recursion Pharmaceuticals,ETH Zurich,Valence Labs, based in United States of America, categorised as academia,Industry,Academia,Industry.
When was Boltz-2 released?
Boltz-2 was published in June 2025.
What is Boltz-2 used for?
Boltz-2 works in Biology, and is recorded as handling protein interaction prediction, Protein-ligand binding affinity 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.
Where can I download Boltz-2?
The weights for Boltz-2 are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
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.