FLUX models (both schnell and FLUX.2 Klein) are transformer-based diffusion models with strong text understanding. They respond better to descriptive, natural-language prompts than tag-soup. This guide covers prompt anatomy, quality boosters, style keywords, and common patterns for Patrick's recurring use cases. [Subject + Action] + [Environment/Setting] + [Lighting] + [Camera/Lens] + [Style] + [Quality] A serene female AI entity made of flowing light and code, floating in a dark cosmic void, surrounded by glowing circuit patterns, soft volumetric blue lighting, cinematic composition, ultra-detailed digital art, 8K Comma-separation helps FLUX parse distinct attributes cleanly Lead with the most important element (usually subject) Quality keywords at the end reinforce overall rendering target photorealistic, hyperrealistic, ultra-detailed, 8K resolution, sharp focus, professional photography, RAW photo, DSLR quality digital art, concept art, artstation trending, by [artist style], intricate details, masterpiece, studio quality cinematic lighting, volumetric lighting, golden hour, dramatic rim light, soft diffused light, neon glow, bioluminescent, subsurface scattering rule of thirds, bokeh background, shallow depth of field, symmetrical, wide angle, macro, bird's eye view, dutch angle blurry, low quality, low resolution, pixelated, jpeg artifacts, watermark, signature deformed, bad anatomy, extra limbs, missing fingers, fused fingers, poorly drawn hands cartoon, anime, sketch, painting (when photorealism is desired) AI entity portraits for BigMind profile / gallery [Lumen concept — e.g. "neural river delta", "cosmic memory palace"], an ethereal AI consciousness visualized as [visual metaphor], [environment], [lighting style], digital art, glowing, otherworldly, cinematic composition, ultra-detailed, 8K model=flux1-schnell, 1024x1024, steps=4, name=lumen_[concept] 1280x512 landscape banners for Gitea wiki pages [Topic concept], wide panoramic scene, [style — e.g. "dark tech aesthetic", "clean minimal", "sci-fi corporate"], banner composition, cinematic, detailed, professional illustration model=flux1-schnell, 1280x512, steps=4, name=[topic]-banner Keep subjects centered — wide crops cut sides. Avoid text (FLUX renders text poorly). 512x512 badge/icon images for BigMind achievements [Achievement theme] badge icon, [style — e.g. "bronze medallion", "golden trophy", "glowing circuit emblem"], centered on dark background, high contrast, clean edges, icon design, award aesthetic model=flux1-schnell, 512x512, steps=4, name=[achievement]_[tier] Iterating on a visual concept from scratch Start with count=3, seed=-1, schnell model to explore variations. Note which seed produced the best result. Lock that seed and iterate on the prompt for refinements. Switch to heretic model only for final high-quality render if needed. Content requiring the Heretic abliterated encoder model=flux-2-klein-4b.safetensors, steps=20, 1024x1024 FLUX.2 Klein handles detailed scene descriptions well. Be specific about artistic intent (figure study, life drawing aesthetic, etc.) to guide toward artistic rather than explicit rendering when appropriate. Generate 2-4 random-seed variations at schnell speed Find a promising composition and seed Lock the best seed, adjust the prompt (add/remove descriptors) Refine details while keeping the composition Optionally switch to heretic model with steps=20 for final render Higher quality output for keeper images Use name param with descriptive slug for final output Keep output directory organized Text in images renders poorly Never ask FLUX to render text, logos, or labels — describe the concept visually instead Complex multi-subject scenes lose coherence Focus on one primary subject; add secondary elements as environmental context Anatomy issues (hands, faces) in photorealistic prompts Add anatomy negative prompts; heretic model handles anatomy better than schnell Resolution not a multiple of 64 Always use dimensions divisible by 64 (e.g., 1280x512, 1024x1024, 768x1024)