I just finished an ambitious project building out a unique Krea2 tiled diffusion approach.The 'secret sauce' is using the qwen3/krea2's vision encoding ability and apply it tile by tile rather than the whole image - giving extremely good cohesion and adherence with the right settings (denoise 0.1-0.2). No text prompt is needed, but another unique ability - you can provide PER TILE text prompt in addition to global - only rely on the image itself with no text - or rely on text only, global and/or per tile.You'll need to install my custom nodes (git clone in your custom nodes folder: <a target="_blank" rel="ugc" href="https://github.com/RandyHaylor/krea2-tiled-diffusion-comfyui">https://github.com/RandyHaylor/krea2-tiled-diffusion-comfyui</a>=== Krea 2 Tiled Diffusion ===Tiled high-res detail pass for Krea 2- Two custom nodesExcellent adherence to the original- Each tile is shown the region it is about to draw- Detail is added, composition is not reinvented- vision_weight 1.0 keeps it close* Up to 8.0 tightens it further* Both usableNo ControlNet, no tile preprocessors, no seam repair- No masking, no regional conditioning nodes- No second model- Load image, upscale, encode, sample* Two of our nodes and ComfyUI's ownTiles recombine inside each sampling step- Others finish each tile, then blend* Tiles already decided content independently* Blending cannot reconcile them- Here all tiles run the same step* Recombined under a raised cosine weight before it returns* Neighbours cannot divergeEach tile is shown only its own region- The encoder looks at that tile's crop, not the full image- Show a tile the whole picture and it draws the whole picture* Usual cause of duplicated subjectsPrompt need not describe the image- Subject comes from what the encoder sees- Complete working prompt for a figure, two katanas, footwear, text blocks* a black and white image in a high quality drawing style- Global prompt applies to EVERY tile* Keep to medium, palette, style- Nine optional per-tile fields* Text in one field affects only that tileMemory scales with the tile, not the canvas- Model never given the full latent- Bigger output = bigger grid, not bigger card- 3x3 reaches high resolutions on cards that cannot hold the whole latentLatent in, latent out- Latent must already be at target resolution- Neither node resizes, crops, or uses a VAE- Inserts into a hires chain with no pixel round trip=== Settings ===Detail pass- 2x2, 256px overlap, 4 steps, 0.10 denoiseRebuild- 2x2, 256px overlap, 8 steps, 0.75 denoiseReduced VRAM- 3x3All three- euler, simple, cfg 1=== Models ===Tested with- krea2TurboRawINT8 — INT8, approx. 12 GB- qwen3vl4bInt8W4a8_int8convrotAlso suitable- Smaller quantised qwen3vl_4b text encoders- Smallest v1.2 identity edit LoRA rank=== Links ===Required custom nodes- <a target="_blank" rel="ugc" href="https://github.com/RandyHaylor/krea2-tiled-diffusion-comfyui">https://github.com/RandyHaylor/krea2-tiled-diffusion-comfyui</a>

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