Z-Image's eye for texture on MiniMax-H3's engine. Drop-in replacements for the standard H3 checkpoints: same identity, same voices, same speed, same VRAM, same workflows - but sets and surfaces render noticeably richer. Peeling paint peels harder, rust bleeds further, water carries more light.

And the extra detail stays flat across chained shots - measured on the same seed, the graft ran a 0.99 texture ratio over three joins where stock drifted to 1.11. More detail, no per-shot sharpening creep from the graft.

What is this, actually

Z-Image is a 6B image model with exceptional fine-texture rendering. Both it and MiniMax-H3 normalise attention queries per head - so the shape of how sharply each attention head commits to fine detail can be transplanted between them by rescaling those normalisation weights. That's the whole trick: no retraining, no new knowledge, H3 keeps everything it knows and attends to texture the way Z-Image does. Early blocks are deliberately left untouched (grafting them creates a weave artifact in tile-like textures - we measured, so you don't have to). This is the second marriage in this line - Joy-LTX 2.5 put JoyAI-Echo's performance on LTX-2.5's engine the same way, donor to engine. The statistics-transplant mechanism here is our own; a nod to TenStrip, whose H3 attention experiments sparked the question of what an image model could donate.

Which file

Two versions on this page - fl2va (default) chains and lands on supplied frames; ref2va adds reference images, voice anchoring and the identity bank for characters that must persist. Every format is attached to its version:

RTX 30 / 40 - take a GGUF (needs ComfyUI-GGUF; the Multishot pack's loader takes both formats):

• curve-zs05-Q8_0 - 21.5 GB - 32 GB cards, closest to full precision.

• curve-zs05-Q5_1 - 15.2 GB - the 24 GB pick.

• curve-zs05-Q4_0 - 11.5 GB - the 16 GB pick.

• plain (non-curve) Q5_1 / Q4_0 (and Q3mix on fl2va) - for workflows built on the original bakes.

RTX 50 - take a comfy-native (stock Load Diffusion Model, ComfyUI 0.32+):

• comfy-int8 - 21 GB - the fastest file on Blackwell, 32 GB cards.

• comfy-fp8 - 21 GB - the fp8 twin (ref2va also ships fp8e5m2).

• comfy-w4a8 / nvfp4 / mxfp8 - ~11-12 GB - the 16 GB family (ref2va also ships w4a4).

• int8_convrot (ref2va) - the Lightricks-style convrot build.

The master: ref2va pruned zs05 bf16 - 40.2 GB - quantise your own cuts from it.

Install

Put the file where your H3 checkpoints live. Pick it in your loader. Done - every H3 workflow works unchanged, including the MiniMax-H3 Multishot seamless-chain canvases.

Links

All formats: the GGUF and comfy-native repos on Hugging Face (joeygambino). Workflows: the MiniMax-H3 Multishot page. Questions: comment here - I answer.