After 35 years of of continuous development, [GRASS GIS](https://grass.osgeo.org/) comes again with great improvements. Being a community-driven project, it offers geospatial analysis, earth observation, time series processing and visualization. It supports large raster files (billions of cells), vector topology, and coupling with SQL databases. In our presentation we'll give an overview of the latest improvements. The algorithms for interpolation, solar radiation, water flow, and sediment transport have been parallelized. Experimental features include concave hull, vector algebra, point cloud import, DEM fusion and blending, object-based classification, Sentinel data processing, and spatio-temporal algebra. Furthermore, pest spread and urban growth modeling are now available. Importantly, Python 3 support has been added. Raster storage now benefits from new ZSTD compression. GRASS GIS supports GDAL up to v2.5 and PROJ up to v6. Easy cloud deployment is offered with ready-to-use docker images and an improved test coverage along with continuous integration. The code development will move to GitHub, including the issues and source code branches since 1987. A new, modern website is on the way, supported by a crowdfunding campaign.