Project AURIONAI Use-Cases Research & Innovation
Fudan University
weather

FuXi

Fudan University cascade weather model targeting the ECMWF ensemble mean at long leads.

Figure from the FuXi paper: Overall architecture of FuXi model.
Levelmodel
Classweather
Parametersnot in the notes
Contextnot in the notes
Released22 Jun 2023
Opennessunknown
Runs onnot in the notes
Statusactive

Benchmark Results

maintainer-run
Z500 day 10, deterministic, FuXi vs ERA5maintainer-run
631.7
0450900

Score in RMSE m2/s2. Lower is better.

year 2020, 240x121 grid10 Oct 2026 researchsites.withgoogle.com
Z500 day 5, deterministic, FuXi vs ERA5maintainer-run
277.1
0450900

Score in RMSE m2/s2. Lower is better.

year 2020, 240x121 grid10 Oct 2026 researchsites.withgoogle.com
Z500 day 3, deterministic, FuXi vs ERA5maintainer-run
125.4
0450900

Score in RMSE m2/s2. Lower is better.

year 2020, 240x121 grid10 Oct 2026 researchsites.withgoogle.com
Z500 day 1, deterministic, FuXi vs ERA5maintainer-run
40.1
0450900

Score in RMSE m2/s2. Lower is better.

year 2020, 240x121 grid10 Oct 2026 researchsites.withgoogle.com
Where this comes from
Every score names who ran it: vendor-reported, maintainer-run or independent. A rank is shown with the population it was ranked in (gap rule 3).

Lineage

successor
Fudan UniversityFuXi-2.1 is a child (successor)medium confidencenotes
Where this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 2 models. Confidence and evidence are the notes' own.

R&D Topics

Identity

Developer
Fudan University
Family
not in the notes
Released
22 Jun 2023 sourcesannouncement page
Weights published
–
Record checked
10 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
dense transformer Cascade machine learning forecasting system for 15-day global forecasts
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
unknown
Licence
not in the notes 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
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.

Industry Use Cases

No industry use case links this model.

Sources

  1. FuXi: A cascade machine learning forecasting system for 15-day global weather forecast arxiv.org https://arxiv.org/abs/2306.12873
  2. China bets on AI weather forecasting as extreme weather intensifies news.tuoitre.vn https://news.tuoitre.vn/china-bets-on-ai-weather-forecasting-as-extreme-weather-intensifies-103260812213327362.htm
  3. AI and weather forecasting: second generation of AI weather models infoplaza.com https://infoplaza.com/en/blog/ai-weather-forecasting-second-generation-ai-weather-models

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "FuXi", https://aurion.semai.id/models/fudan-university-fuxi/, records of October 2026.