LTX-2.5 22B Distilled — NVFP4 ComfyUI-ready, V2 (keyframes edition)
Caught 'em lacking. On a Sunday.
The updated official NVFP4 export (2026-08-16, "Restore keyframes support") — stamped so ComfyUI actually loads it. Again.
The saga so far
- Aug 11 — LTX-2.5 drops. The official NVFP4 transformer won't load in ComfyUI: the packed FP4 weights get read as dense bytes and you eat a
mat2shape error. I stamp per-layer.comfy_quantmarkers onto it and publish V1 — the first working comfy NVFP4 on the Hub. - Aug 12 — the official file quietly grows the exact same markers (discussion #16 👀). Respect. They also notice the export dropped the keyframe positional embedding and pull the config flag.
- Aug 16, 12:19 UTC, a Sunday — "Restore keyframes support": the official file gets replaced with a keyframes-capable re-export. Fresh quantization, embedding restored... and the ComfyUI markers are gone AGAIN. Launch-day crash, the sequel.
- Aug 16, a few hours later, still Sunday — caught 'em lacking on the Lord's day. This repo: the new payload, stamped, render-verified, keyframes and all. Y'all have got to start test-loading these in Comfy before you hit upload. 🙏
What this is
The current official ltx-2.5-22b-distilled-transformer-nvfp4.safetensors (keyframes-capable 2026-08-16 re-export) with ComfyUI's per-layer {"format": "nvfp4"} .comfy_quant markers added. Weights, scales, and license metadata untouched. 7,877 tensors, 1,176 quantized layers stamped — and the headline vs V1: keyframes_abs_pos_embedding is back in the file.
Verified before upload (RTX 5090, ComfyUI 0.33)
First/last-keyframe (flf2v) bridge rendered with this exact file — two keyframes in, the model fills the 5 seconds between:
- flf2v: 5s @ 1280×736 in ~55s wall with SageAttention 3.
- t2v / i2v load and render clean in the standard LTX-2.5 template graphs (plain
UNETLoader).
Same seed, same prompt, both quants
10 seconds @ 1280×736, seed 910090 on both. Similar and close, not identical — and the 4-bit file is ~3GB lighter.
V1 or V2?
This one. V1 was built from the pre-keyframes export — it still works for t2v/i2v, but it physically does not contain the keyframe embedding. V2 is the current official payload, so new pulls should come here.
Usage
Drop the file in models/diffusion_models/, select it in UNETLoader in any LTX-2.5 template graph. Example t2v API workflow included in the repo.