graphfamily
GraphGPS
Recipe for general, powerful and scalable graph transformers that combine message passing with global attention. Paper by Rampasek et al. (2022).
Levelfamily
Classgraph
Parametersnot in the notes
Contextnot in the notes
Released25 May 2022
Opennessopen source
Runs onnot in the notes
Statusactive
Identity
- Developer
- Mila, Universite de Montreal
- Family
- not in the notes
- Released
- 25 May 2022 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- GNN Local message passing combined with global attention
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- graph
- Output
- graph
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open source
- Licence
- MIT License sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Licence is that of the authors' rampasek/GraphGPS repository (MIT).
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
ModelGraphGPSMila, graph
GraphGPSMila, graphUse Casesnone recorded
Who Runs Itnone recorded
Sources
- arxiv.org/abs/2205.12454 https://arxiv.org/abs/2205.12454
- github.com/rampasek/GraphGPS https://github.com/rampasek/GraphGPS
- GitHub - pyg-team/pytorch_geometric: Graph Neural Network Library for PyTorch github.com https://github.com/pyg-team/pytorch_geometric
- pytorch-geometric.readthedocs.io/en/latest/modules/nn.html https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html
- arxiv.org/html/2205.12454 https://arxiv.org/html/2205.12454
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "GraphGPS", https://aurion.semai.id/models/graphgps/, records of October 2026.