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Nvidia's 332M-parameter AI model emulating the SCREAM global storm-resolving atmosphere simulation at ~4.9 km, 10-minute steps.

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STRATA at a glance

What is STRATA?
STRATA is a model from Nvidia. Nvidia's 332M-parameter AI model emulating the SCREAM global storm-resolving atmosphere simulation at ~4.9 km, 10-minute steps.
Who makes STRATA?
STRATA is made by Nvidia.
Does STRATA work in the EU?
Available in the EU. Open weights downloadable from Hugging Face under OpenMDW 1.1 with deployment geography listed as "Global"; no EU exclusion found in the license or model card. Last verified 14 Nov 2026.
How much does STRATA cost?
Open source. Free to download; the model card states it is ready for commercial or non-commercial use. Licence: OpenMDW-1.1.
Where was STRATA shown?
In 1 creator video by AI Search. Most recently by AI Search on 8 Nov 2026, at 5:09 in “Weight space programming, new 3D models, Gemini Omni 1.2, GPT Image 2.6: AI NEWS”.

Sources: the vendor's own pages (linked above) and creator videos at the linked timestamps. EU status is information, not legal advice; see how we check.

About

STRATA (Storm-resolving Tile-based autoRegressive Atmosphere Transformer Architecture) is a global, kilometer-scale AI atmosphere model from Nvidia, published as part of the Earth-2 checkpoints. It emulates the SCREAM (Simple Cloud-Resolving E3SM Atmosphere Model) storm-resolving simulation, autoregressively predicting the 3D atmospheric state on SCREAM's ne1024pg2 cubed-sphere grid (about 25.2 million columns, ~4.9 km spacing) with a 10-minute time step.

The prognostic state covers potential temperature, zonal and meridional wind, geopotential height, vertical pressure velocity and specific humidity on 24 model levels, plus 2-m air temperature. Surface pressure and surface precipitation fluxes are diagnosed at each step. The architecture is a two-stage "PixelDiT" transformer with neighborhood attention (331.7M parameters), a deterministic single-step predictor trained with a regression loss and fine-tuned with 4-step autoregressive rollouts; no diffusion sampling is used.

Inference is tile-based: a single GPU can advance any part of the globe, and multi-GPU domain decomposition advances the full globe. Intended uses are weather and climate research, such as short-range forecasting of the SCREAM state, emulation of storm-resolving simulations, and experiments in coupling or downscaling AI emulators. Weights are on Hugging Face under the OpenMDW 1.1 license; training recipes and inference code are in the NVlabs/STRATA repository, and the architecture is in NVIDIA PhysicsNeMo.

Key features
  • Global atmosphere emulation at ~4.9 km (ne1024pg2 cubed-sphere grid)
  • 10-minute autoregressive time step
  • 331.7M-parameter two-stage transformer with neighborhood attention
  • Tile-based inference on a single GPU or multi-GPU domain decomposition
  • Weights released under OpenMDW 1.1; code under Apache-2.0
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