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Chapter 13. Validated models for geospatial inference with TerraTorch

The following IBM and NASA Prithvi geospatial foundation models are validated for use with AI Inference Server and TerraTorch.

Note

Prithvi-EO-2.0 models use the Vision Transformer (ViT) architecture and require TerraTorch as the model implementation backend. These models accept GeoTIFF imagery as input and return segmentation predictions.

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Table 13.1. Prithvi geospatial models for use with TerraTorch
ModelUse caseHugging Face model cardValidated on

Prithvi-EO-2.0-300M-TL-Sen1Floods11

Flood detection and mapping

Prithvi-EO-2.0-300M-TL-Sen1Floods11

RHAIIS 3.3

Prithvi-EO-2.0-300M-BurnScars

Burn scar detection

Prithvi-EO-2.0-300M-BurnScars

RHAIIS 3.3

Explore the IBM and NASA geospatial models collection on Hugging Face.

Important

Prithvi geospatial models are validated for use with NVIDIA CUDA AI accelerators only.

These models require specific vLLM server arguments to function correctly. You must include --skip-tokenizer-init, --enforce-eager, and --enable-mm-embeds when starting the inference server.

For the complete list of required server arguments, see TerraTorch configuration options for geospatial model serving and Serving TerraTorch Models with vLLM.

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