Mikey Sampler Tiled

If you've built an SDXL hi-res-fix chain by hand - base sample, refiner pass, upscale with a model, tiled re-sample for detail - you know it's four or five nodes wired together with room to get any one of them wrong. Mikey Sampler Tiled collapses that entire chain into a single node. It's genuinely one of the reasons people reach for this pack in the first place: on r/StableDiffusion, when a beginner asked how to add hi-res upscaling to their workflow, the top practical answer was simply "grab the Mikey nodes, then switch your VAE Decode with the Mikey sampler tiled advanced" - that's how directly this family of nodes gets recommended as the shortcut for exactly this problem.

The mechanism, per the author's own description: base model generates, refiner model refines, an upscale model enlarges the result, and then a tiled resample pass over the enlarged image adds detail back in - with a built-in complexity check meant to stop the final pass from over-cooking simple, flat areas (faces especially) into a scrambled mess. It's the classic SDXL base→refiner two-stage pipeline, which the wider community has largely stopped bothering with once fine-tuned checkpoints matured - so if you're on a modern single-stage SDXL fine-tune, you can wire your base model into both the base_model and refiner_model slots and it'll still work, just without the "real" refiner behavior.

The inputs that matter: base_model and refiner_model, plus the four conditioning inputs (positive_cond_base, negative_cond_base, positive_cond_refiner, negative_cond_refiner) - yes, base and refiner get separate conditioning, which is standard SDXL practice. model_name is your upscale model, pulled from ComfyUI/models/upscale_models - the README specifically recommends "lollipop" for a balanced result, or NMKD Superscale / 4x-UltraSharp if you want sharper detail; grab them from OpenModelDB. upscale_by sets your target scale (1 = original size). tiler_denoise (default 0.25) controls how aggressively the tile pass reworks detail - this is the setting most likely to scramble a face if you push it too high, so start low and nudge up only if the result looks flat. tiler_model picks whether the tile pass uses the base or refiner model. Two outputs: tiled_image (the final result) and upscaled_image (the pre-tile upscale, handy for A/B comparison).

Installing it

Through ComfyUI Manager, search "Mikey Nodes." Manually:

cd ComfyUI/custom_nodes
git clone https://github.com/bash-j/mikey_nodes

Restart ComfyUI. The one real dependency this specific node has: an upscale model in ComfyUI/models/upscale_models. The pack doesn't ship one - you need to download it yourself from OpenModelDB and drop it in that folder before model_name has anything to select.

Common issues

Forgetting the upscale model download is the number one reason this node fails on first run - model_name will simply have nothing valid to pick if the folder's empty. Second most common: tiler_denoise set too high, which is precisely the scrambled-face problem the node's built-in complexity detection is trying to guard against - if faces are coming out warped after the tile pass, dial it down toward 0.15–0.2 before touching anything else. And if you want more control than this node exposes - explicit steps, cfg, sampler and scheduler choice, or the option to skip generation and just tile-upscale an existing image - that's exactly what MikeySamplerTiledAdvanced is for; this node is the deliberately simpler, fewer-knobs version of it.