Model type
Biomolecular structure and affinity predictor
Model
Boltz-2
Boltz predicts biomolecular complex structures; Boltz-2 also predicts binding affinity.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 LimitationsHow it worksBoltz-2 workflow
Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 LimitationsOverview
Inputs
Protein, nucleic-acid and ligand specifications in prediction input files.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 LimitationsOutputs
Predicted complex structures and, for supported Boltz-2 inputs, binding-affinity predictions.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 LimitationsAccess
Official project documentation and implementation: https://github.com/jwohlwend/boltz
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitationslimited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Evaluations and results
1 evaluation · 1 metric rows. Different protocols are not a single leaderboard.
Filter evaluations
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Boltz-2 | Task: Ligand potency prediction using generated poses Dataset: SARS-CoV-2 Mpro ligands | 0.800 Pearson R unitless · unknown Uncertainty: ± 0.027 Coverage: Not reported scored / Not reported eligible | Independent external evaluation · source checkedMethods, coverage and sourceBoltz-2: Ligand potency prediction using generated poses Potency prediction using Boltz-2 ligand-pose generation protocol; see paper scoring pipeline. Aggregation: Not reported A Comparative Study of Deep Learning and Classical Modeling Approaches for Protein–Ligand Binding Pose and Affinity Prediction in Coronavirus Main Proteases · Table 3, Boltz-2 row, Pearson’s R column |
Source checking is not independent reproduction. Release 2026-09-23-2b89723c6dd9.
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How it works, versions and access
Related profile: Boltz. This page retains the exact record and its evaluation context.
Versions and evaluated configurations
- Boltz-2 · family
How it works
How it works
Boltz-2 first encodes the molecular inputs, alignments and optional templates into token and pair features. A Pairformer trunk updates those features and conditions atom-coordinate diffusion to generate a complex. Separate confidence and affinity modules assess the prediction; affinity classification and regression outputs answer different questions.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 LimitationsVersions and reproducibility
Boltz-1 and Boltz-2 are distinct released generations; the catalogue does not select an evaluated checkpoint. The Boltz-2 report describes training crops up to 768 tokens. This is a training-crop size rather than a universal inference maximum; affinity additionally uses a pocket crop.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 LimitationsStrengths, limitations and unresolved questions
Strengths and limitations
Strengths and considerations
- The project distributes prediction code, model weights and training instructions.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations
Limitations and conditions
- Affinity predictions depend on a plausible binding pose and mix biochemical endpoint types. The report notes limited handling of cofactors, water and multimeric binding partners, and substantial variation between assays.
Sources (6)
jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations
Profile review details
Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied.
Stable record: catalog-model-boltz-2Specifications
Inputs, training, access and other details
Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Model type | Biomolecular structure and affinity predictorSources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Architecture | Molecular input embeddings, MSA and optional template modules build single-token and pair representations. Pairformer blocks refine these features; atom-coordinate diffusion generates structures, with separate confidence and binding-affinity modules.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Inputs | Protein, nucleic-acid and ligand specifications in prediction input files.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Outputs | Predicted complex structures and, for supported Boltz-2 inputs, binding-affinity predictions.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Parameters | A complete parameter total is not stated in the reviewed Boltz-2 architecture report or model constructor; structure, confidence and affinity are separate modules. · Not reported in inspected sourcesSources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Known versions | Boltz-1 and Boltz-2 are distinct released generations; the catalogue does not select an evaluated checkpoint.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Training data | Boltz-2 structure training combines pre-June-2023 PDB entries, MISATO/ATLAS/mdCATH molecular dynamics, and AlphaFold2/Boltz-1 distillation. Separate affinity training uses curated PubChem, ChEMBL, BindingDB, HTS, CeMM and MIDAS evidence with different regression/classification labels.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Training cutoff | Boltz-2 experimental PDB structures were released before 2023-06-01. This is not a shared cutoff for every affinity, MD or distilled resource, nor a Boltz-1 training cutoff.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Context limits | The Boltz-2 report describes training crops up to 768 tokens. This is a training-crop size rather than a universal inference maximum; affinity additionally uses a pocket crop.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Weights licence | MIT; the README explicitly applies this licence to code and model weights.Sources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Access | Official project documentation and implementation: https://github.com/jwohlwend/boltzSources (6)jwohlwend/boltz: README.md; jwohlwend/boltz: docs/prediction.md; jwohlwend/boltz: docs/training.md; jwohlwend/boltz: src/boltz/model/models/boltz2.py; jwohlwend/boltz: scripts/train/configs/full.yaml; boltz2: Journal full-text XML · src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations |
| Code licence | MITSourcesjwohlwend/boltz: LICENSE · LICENSE: licence text |
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Evidence table
Inspect claims, sources and review details
Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
116 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims | jwohlwend/boltz: docs/training.md src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
| Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims | jwohlwend/boltz: docs/prediction.md src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
| Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims | jwohlwend/boltz: src/boltz/model/models/boltz2.py src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
| Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims | jwohlwend/boltz: scripts/train/configs/full.yaml src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
| Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims | boltz2: Journal full-text XML src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: preprint; 1 | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
| Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims | jwohlwend/boltz: README.md src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Diagram steps
| jwohlwend/boltz: docs/training.md src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Diagram steps
| jwohlwend/boltz: docs/prediction.md src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Diagram steps
| jwohlwend/boltz: src/boltz/model/models/boltz2.py src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Diagram steps
| jwohlwend/boltz: scripts/train/configs/full.yaml src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc | source checked automated source review · 2026-09-16 Audit detailsInspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Sources and history
View linked audit checks and correction history
Release 2026-09-23-2b89723c6dd9 · Record review: discovered
8 source records and release history
- Boltz-2 official resource · Original source · Not reported
- jwohlwend/boltz: README.md · Original source · b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc
- jwohlwend/boltz: docs/prediction.md · Original source · b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc
- jwohlwend/boltz: docs/training.md · Original source · b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc
- jwohlwend/boltz: src/boltz/model/models/boltz2.py · Original source · b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc
- jwohlwend/boltz: scripts/train/configs/full.yaml · Original source · b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc
- boltz2: Journal full-text XML · Original source · preprint; 1
- jwohlwend/boltz: LICENSE · Original source · b1ebfc46ecf57f5414e0d1a6f9027bbb122c53bc
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
- historical missing metadata
- checkpoint revision: not_yet_extracted; training data: not_yet_extracted; licence: not_yet_extracted
- metadata review scope
- historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
- entity classification
- review date: 2026-09-17; rationale: The cited profile describes a named learned biological predictor or representation model/family. Preserve this identity separately from task-specific fitting, individual checkpoints, pipelines and hosted access.; source ids: evidence-official-f780521ccebbb0691f9e; evidence-official-5a9e55abdf288d9dd8da; evidence-official-39a15ed8072aeea14a22; evidence-official-734117ed8501eb26fefc; evidence-official-7cb8cb7f091536b92c11; evidence-official-bd6ec1f819e22f075c32; source locator: src/boltz/model/models/boltz2.py: Boltz2.__init__, forward, PairformerModule, AtomDiffusion and AffinityModule; docs/prediction.md: affinity outputs; Boltz-2 report Sections 2 Data, 3 Architecture, 4 Training and 6 Limitations; ambiguities: None recorded
Related records
- variant of: Boltz
- subject: Boltz-2: variant of Boltz
- family: Boltz-2