IBM and NASA Release Open-Source AI Model to Support Lunar Exploration

• The NASA‑IBM Lunar Foundation Model turns decades of lunar observations into a foundation for discovery, helping scientists surface patterns across data at a scale no single instrument has provided

• The model exceeds widely used methods by up to 23% in identifying key geographic features on the Moon’s surface, including potential ice deposits, craters and volcanic formations, to support a sustained return to the Moon

Sep 10, 2026

YORKTOWN HEIGHTS, N.Y., SEPT 10, 2026 – IBM (NYSE: IBM) and NASA today announced the open-source release of the NASA‑IBM Lunar Foundation Model, one of the first publicly available foundation models for scientific exploration of the Moon, now available. Trained on an extensive lunar observation dataset curated by IBM and NASA researchers, the model can help scientists turn decades of complex, multi-instrument data into insights to support the establishment of a sustained human presence on the Moon.

The Moon’s topography is ever-changing. Over time, the Moon’s surface has formed craters, distributed ice and even experienced volcanic activity. For decades, sensors and instruments have continuously observed the Moon, generating petabytes of data, but to study the Moon’s surface, scientists need to either sift through maps and images by hand or use low resolution, task specific machine learning models. These methods can be computationally intensive and can lack the degree of scientific accuracy needed to identify and analyze geographic features. The newly released NASA-IBM Lunar Foundation Model will help researchers accelerate scientific progress by identifying hidden relationships between many different types and resolutions of lunar data.