weather
FourCastNet 3
Probabilistic ensemble global weather model that NVIDIA reports as 8 to 60 times faster than comparable approaches. Paper by Bonev et al. (2025).
Levelvariant
Classweather
Parametersnot in the notes
Contextnot in the notes
Released16 Jul 2025
Opennessopen weights permissive
Runs onnot in the notes
Statusactive
R&D Topics
Identity
- Developer
- NVIDIA
- Family
- FourCastNet
- Released
- 16 Jul 2025 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
- other Geometric probabilistic ensemble forecasting
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- sensor
- Output
- sensor
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 weights permissive
- Licence
- Apache License 2.0 sources
- Access routes
- open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- not in the notes
- 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
DeveloperNVIDIAbig tech, USA
NVIDIAbig tech, USAModelFourCastNet 3NVIDIA, weather
FourCastNet 3NVIDIA, weatherR&D TopicsProbabilistic Ensemble Weather Forecasting with Machine LearningMachine-Learning Medium-Range Weather Forecasting
Use CasesWeather ForecastingAgricultureUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)Contract signed, 5 Feb 2026Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)In production, 23 Sep 2025Deployments of these use cases; none names this model.
Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)Contract signed, 5 Feb 2026Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)In production, 23 Sep 2025Deployments of these use cases; none names this model.Models 1
Organisations 1
R&D topics 2
Machine-Learning Medium-Range Weather ForecastingGlobal forecast models learned from reanalysis data that predict the next 10 to 15 days m…produced byProbabilistic Ensemble Weather Forecasting with Machine LearningMachine-learning models that produce many possible weather futures, giving forecast uncer…exemplar
Sources
- arxiv.org/abs/2507.12144 https://arxiv.org/abs/2507.12144
- huggingface.co/nvidia/fourcastnet3 https://huggingface.co/nvidia/fourcastnet3
- ai.azure.com/catalog/models?task=weather-forecasting https://ai.azure.com/catalog/models?task=weather-forecasting
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "FourCastNet 3", https://aurion.semai.id/models/nvidia-fourcastnet-3/, records of October 2026.