YouTube: https://youtu.be/b0LXyla0fuc Flux 2 Klein is here — and it’s a major upgrade for AI clothes swapping in ComfyUI. In this video, I compare Flux 2 Klein vs Qwen Edit 2511 side-by-side and zoom in on the things that actually matter: fabric texture (like lace), hair detail, and how well lighting and shadows match the scene. In many cases, Klein not only looks sharper, but also generates faster and handles large 2048×2048 outputs more reliably than older Qwen Edit workflows. After the comparison, I jump into ComfyUI and walk through the workflow. We’ll do real examples like swapping a trench coat onto a target photo, removing unwanted accessories (without messing up coat accuracy like button count), and fixing tricky cases where pose differences can cause issues like extra hands. I’ll also show the optional high-res fix node group for a final upscale pass to squeeze out a bit more detail. Join our paid group to get the workflow: https://myaiforce.com/pg

Meet Flux 2 Klein, Black Forest Labs’ newest (and fastest) image model—built for text-to-image + image editing, and able to run on consumer GPUs with ~13GB VRAM. In this video, I break down why Klein can be amazing but also prone to classic anatomy fails (extra fingers, weird hands, etc.). After generating hundreds of test images on RunningHub, I’ll show you the best ComfyUI settings I found to reduce those mistakes—plus how samplers, step counts, and CFG change the final look. You’ll also see a quick head-to-head vs Z Image Turbo (prompt-following, skin texture, speed, and batch variety). YouTube: https://youtu.be/xgbCRQuxUMk ✅ Free workflow download below Welcome to join our paid group: https://myaiforce.com/pg

YouTube: https://youtu.be/ZphPp-9ou34 Learn how to do high–success-rate pose transfer with Qwen Edit in ComfyUI—even for tricky poses. I’ll walk through my full workflow (hosted on RunningHub), starting with the basic setup and then upgrading it with DWPose skeleton refs, two HuggingFace LoRAs (base + helper), and smart masking to protect face/hair consistency. Finally, we’ll polish the result using Face Detailer for better gaze + identity match. Join our paid group to get the workflow: https://myaiforce.com/pg

YouTube: https://youtu.be/ntmSNkKEoy8 Pixel drift is still a big issue with Qwen Edit (even 2511)—tiny shifts, zooms, or misalignment that ruin pixel-perfect edits. In this video, I break down multiple no-drift methods that fix alignment and improve quality by restoring original details. ✅ What you’ll learn: How to do global edits (full image changes) with perfect pixel alignment A clean local editing method (inpainting crop → edit → stitch back) that avoids drift entirely Join our paid group to download this workflow: https://myaiforce.com/pg

YouTube: https://youtu.be/sejIPfdMNv8 Happy New Year! 🎉 In this video, we test the updated Qwen Image Edit v2511 and answer the big question: is it actually better than v2509? You’ll see side-by-side comparisons in ComfyUI (same seed, same CLIP/VAE) to evaluate consistency, identity preservation, and overall image quality. We also break down the real-world differences between model formats and sizes—including BF16, FP8, FP8 Lightning, GGUF (Q6/Q4), and Lightning LoRA—so you’ll know what matters for quality, speed, and VRAM. Finally, we explore sampler + scheduler combos (including Flow Match Euler Discrete Scheduler) to show how much they can change composition, depth, and lighting—even with the same prompt. ✅ All workflows shown are attached.