1. Neutral landscape models have many applications in ecology, such as supporting spatially-explicit simulations, developing, and evaluating landscape indices. However, current approaches provide few options to produce large landscapes with controlled composition and fragmentation indices. 2. We introduce flsgen (Fragmented Landscape Generator), a new neutral landscape generator that address this limitation by providing a high level of control over 14 landscape indices. The main novelty of flsgen is the decomposition of landscape generation into two steps: the solving of a constraint satisfaction problem and the generation of a landscape raster with a stochastic algorithm. The latter relies on a continuous environmental gradient that influences the landscape’s spatial configuration. 3. flsgen can generate fine-grained artificial landscapes in small amounts of time, which makes it suited to produce large landscape series systematically. We demonstrate the features of flsgen through three illustrative use cases. 4. flsgen is a practical and efficient tool that expand the current possibilities of neutral landscape models and widen their potential applications. To facilitate its uptake, flsgen is available as free and open-source software through a Java API, a command-line interface, or an R package.