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Boltz-2

Boltz is a biomolecular interaction model family. Boltz-2 adds affinity prediction to complex-structure prediction.

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Shared profile: Boltz. This page retains the exact record and its evaluation context.

At a glance

Explanatory profile: source reviewed · Automated source review, 2026-09-16. This does not change the review status of its results.

Inputs, outputs and configuration
PropertyDescription and evidence
AccessRepository states code and models use the MIT licencejwohlwend/boltz official source · README.md: Introduction, Inference, Understanding the affinity prediction and License
Configuration in this recordreleased weightsjwohlwend/boltz official source · README.md: Introduction, Inference, Understanding the affinity prediction and License
Model typeNot extracted or verified for this record.
Training dataNot extracted or verified for this record.
Context limitsNot extracted or verified for this record.
Code licenceNot extracted or verified for this record.
Weights licenceNot extracted or verified for this record.

How it works

Conceptual procedure

Schematic of the documented input, computation and output; not an executable configuration.

Conceptual procedureMolecular inputs. Then: MSA / Pairformer features. Then: Coordinate diffusion. Then: Structure. Then: Separate affinity moduleMolecular inputsMSA / Pairformer featuresCoordinate diffusionStructureSeparate affinity module
Read the diagram as text
  1. Molecular inputs
  2. MSA / Pairformer features
  3. Coordinate diffusion
  4. Structure
  5. Separate affinity module
jwohlwend/boltz official source · Pinned repository src/boltz/model/models/boltz2.py, module construction and forward; README affinity prediction

Boltz-2 architecture

The Boltz-2 implementation combines molecular and alignment features with a Pairformer module. A conditioned diffusion module predicts coordinates; a separate affinity module produces binding outputs. This architecture description applies to Boltz-2, not automatically to every Boltz family release.

jwohlwend/boltz official source · src/boltz/model/models/boltz2.py at the pinned repository revision: MSAModule, PairformerModule, DiffusionConditioning and AffinityModule; README Inference

The documented YAML input describes the biomolecules and requested properties. Structure prediction and affinity outputs are distinct: one affinity output estimates binding strength, while another classifies binders against decoys.

jwohlwend/boltz official source · README.md: Introduction, Inference, Understanding the affinity prediction and License

Benchmarks and results

Release 2026-09-16-d74d282221a9 · 0 evaluations · 0 metric rows. Different protocols are not a single leaderboard.

No evaluations linked in this release.

Strengths and limitations

Strengths supported by sources

  • Supports structure and affinity workflows in one openly distributed project.jwohlwend/boltz official source · README.md: Introduction, Inference, Understanding the affinity prediction and License

Limitations and conditions

  • Binder probability and affinity regression are trained with different supervision and must not be compared as the same metric. Unqualified CLI calls select the latest model.jwohlwend/boltz official source · README.md: Introduction, Inference, Understanding the affinity prediction and License
Profile review details

Primary project documentation or paper inspected for the explanatory claims and cited locations. Reviewed coverage concerns this narrative, not complete metadata, independent reproduction or a performance ranking.

Stable record: catalog-model-boltz-2

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: discovered

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Technical metadata and extraction receipts

Stable ID: catalog-model-boltz-2

areas
molecular-interactions
method types
foundation model
entity level
family
version
released weights
reported name
Boltz-2
access
Public MIT code and weights; substantial compute required.
method type
foundation model
missing metadata
checkpoint revision: not_yet_extracted; training data: not_yet_extracted; licence: not_yet_extracted
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