Native Generation of Tileable Pixel-Art Textures from a Material Name and a Target Colour

Game and mod textures are authored natively at tiny canvases: a 16×16 tile is not a downscaled photograph but a grid in which every pixel is a design decision, the palette holds at most a handful of slots, and the tile must stay continuous across its own wrap boundary because it is used tiled. We study the task of painting a solid-colour region of an image with a tileable pixel-art texture given only a material name and the region's colour, and we generate it natively at the target resolution rather than rendering large and downsampling. Our model decodes palette-index and luminance-rank tokens in parallel, keeps tileability by construction through a toroidal relative attention bias that adds no parameters, and conditions on palettes retrieved from a memory of artist palettes. Against the strongest render-and-downsample pipeline, annotators prefer our 16×16 tiles in 73.6% of decided pairs; on the region-colouring task the de-biased judge prefers them 60.3% (family interval excludes 0.5), and that judge's 57.3% on the name-to-texture comparison is a lower bound on the same human reading. The tiles also win the majority of judge comparisons against a same-data pixel diffusion model, score distillation, and artist-tile retrieval. Measured end to end, a tile takes 0.51 s, 28× faster than the strongest render pipeline and four orders of magnitude faster than score distillation. Getting these comparisons to mean anything required repairing the rulers: we show that render-and-downsample baselines collect a structural gain purely from a larger canvas, that a widely used tiling score awards a perfect value to a flat fill, and that a pairwise judge's resolvable-rate floor is far below chance.