SDXL, SD 1.5, samplers, CFG, steps, hires fix, checkpoints, LoRA and ControlNet — everything in one place.
Negative prompts are not a copy-paste mega list. This guide gives scenario-specific templates for portraits, hands, text, low-res and video stability, plus weight syntax and how SDXL, SD 1.5, Flux and Midjourney differ.
Read full articleA complete teardown of a portrait AI prompt — identity, clothing, scene, soft window light, shallow depth of field — with three rewrites (barista, bookstore owner, night street), five pitfalls and a Midjourney/SDXL/Flux parameter table.
Read full articleSDXL and Flux Dev are the two main open-source image models. This article compares them on quality, speed, LoRA ecosystem, prompt friendliness and commercial licensing.
Read full articleStable Diffusion offers many samplers. This article compares four production-grade options — Euler a, DPM++ 2M Karras, UniPC, DDIM — with recommended step counts.
Read full articleCFG scale controls how literally Stable Diffusion follows the prompt. This article compares four reference values and per-model sweet spots for SD 1.5, SDXL and Flux.
Read full articleSampling steps control how many denoising iterations Stable Diffusion runs. This article gives per-sampler sweet spots and explains when to push higher.
Read full articleHires fix is Stable Diffusion's key way to push resolution. This article covers upscale ratio, denoising strength, and choosing between Latent, 4x-UltraSharp and ESRGAN.
Read full articleThere are hundreds of SDXL checkpoints. This article picks the most reliable ones across realistic portrait, anime, landscape and illustration, with selection notes.
Read full articleLoRA is a small add-on model that gives Stable Diffusion a specific style, character or concept. This article explains weight, trigger words, multi-LoRA stacking and common pitfalls.
Read full articleBREAK is Automatic1111's prompt grouping keyword. This article explains how to use BREAK to bypass the 75 token limit and structure long prompts.
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