Text-to-Image · Prompt Adherence challenges
Every text-to-image challenge testing Prompt Adherence, scored with TrueSkill as the votes come in.
Geometric Composition
A spatial-reasoning test. Each object has a precise relationship (inside, on top, behind, seen through the glass), so it measures whether a model follows explicit placement instructions and handles transparency and refraction rather than just approximating the scene.
Isometric Miniature Diorama Scenes
Combines a strict isometric viewpoint, clean PBR-style materials, and embedded text in one tightly framed scene. It tests whether a model holds a consistent 45-degree perspective, renders the labels accurately, and keeps the composition centered and uncluttered.
Modern Clean Menu
A layout and typography test. The model has to produce a clean, professional menu with legible text, a clear three-section grid, and food imagery that looks intentional, which separates real design sense from a default template look.
Adorable Baby Animals in Sunny Meadow
A multi-subject photorealism test. Four distinct animals must each keep correct anatomy and detailed fur while interacting naturally in one scene under warm directional light. The usual failure points are blended or malformed animals and fur that turns mushy.
Apollo 11: Journey to Tranquility
A structured infographic test. The model must place six labeled steps in order, hold a consistent flat-vector icon style, and render several short labels (step names, crew names, Tranquility) accurately. It rewards layout discipline and punishes garbled text.
Magic Burger Explosion: Fiery Photorealism Challenge
This prompt forces models to simultaneously nail a highly specific, multi-layered commercial scene: dynamic exploded composition with multiple flying food elements, photorealistic textures, dramatic fiery lighting with embers, and precisely integrated glowing text, all while keeping strong visual impact. It is a perfect stress test that quickly separates models with true prompt mastery and creative control from those that miss details, break physics, or produce generic results.
The Capybara Taxi Driver
This challenge seems to be difficult for models because it mixes reality with fiction. Most models struggle to keep the taxi realistic or loose instructions like placing the passenger not in the backseat.
Chalkboard Menu
This challenge forces models to use one consistent handwritten style across an entire dense menu instead of defaulting to clean printed text for the smaller details, a very common failure that reveals how well they actually understand and maintain stylistic coherence.
The Reversed Rodeo
This competition tests how well AI image models truly understand language versus how much they rely on visual habits from their training data. The prompt is deliberately simple on the surface but devilishly hard in practice. Most models default to the familiar trope of an astronaut riding a horse. By forcing the reversal, we measure three critical capabilities that separate good models from great ones: Strict instruction following (including negations) Accurate subject-object relationships and spatial hierarchy Resistance to strong dataset biases