Joy-LTX 2.5 x Z-Image β surfaces, textures, fine details, foliage
The purpose of this merge is surface rendering. Z-Image's spatial attention profile is grafted onto the Joy-LTX 2.5 engine so that straw holds individual strands at mid-distance, foliage reads as leaves instead of green mass, ground litter stays physical, and skin keeps its unretouched grain β while identity, motion, sound and the engine's behavior stay exactly what Joy-LTX 2.5 already was.
This is the same marriage already shipped for MiniMax-H3
(MiniMax-H3-x-Z-Image-native),
applied to the LTX-2.5 line: Z-Image (Lumina2, 6B, exceptional texture rendering)
donates a per-block statistics profile β row norms of its fused-QKV q-slice,
mean-normalized, depth-interpolated to 48 blocks β which rescales this DiT's own
q_norm weights by small per-block factors (clip [0.85, 1.18], dose 0.5). No
retraining, no new knowledge, no architecture change, no Z-Image weights at
inference.
What to expect (calibrated honestly)
Same-seed A/Bs against stock Joy-LTX 2.5 v2 show a consistent, measurable surface win: +8β23% fine-detail energy on matched frames, clearest on hay, foliage, gravel and fabric at mid-distance. It is a paused-frame visible improvement β side-by-side stills show it plainly; in motion it reads as "richer" rather than dramatic. Blind reviewer panels score both arms close, which is exactly the intent: nothing about the render changes except how well surfaces resolve. Comparison stills are attached from the same-seed pairs.
Files (this repo: comfy-native + bf16)
| file | format | note |
|---|---|---|
| ...-v2-zgraft05-DiT-bf16 | bf16 master | archival / requant source |
| ...-v2-zgraft05-DiT-comfy-int8 | int8 | the fast pick on RTX 50 |
| ...-v2-zgraft05-DiT-comfy-fp8 | fp8 | Ada/Blackwell |
| ...-v2-zgraft05-DiT-comfy-nvfp4 | 4-bit | Blackwell-native, emulated elsewhere |
| ...-v2-zgraft05-DiT-comfy-w4a8 / w4a4 | 4-bit | 16 GB cards; w4a8 is the quality pick |
| ...-v2-zgraft05-DiT-comfy-mix4x8-13.8GB / 17.0GB | mixed | VRAM-fitted mixes |
RTX 30/40 (Ampere): use the GGUF repo instead β K-quants run 4β8x faster than any emulated 4-bit arm there.
Drop-in for any Joy-LTX 2.5 v2 workflow β same loaders, same settings, same seeds.
Same-seed comparisons (stock top row, graft bottom row - pause and look)
Model tree for joeygambino/joyai-echo-ltx25-x-Z-Image-native
Base model
Lightricks/LTX-2.5