LTX-2.5-Distilled-Q8_0.gguf
LTX 2.5 Distilled GGUF Q8_0 (Community)
Community Q8_0 GGUF quantization of the LTX 2.5 distilled transformer — the highest-fidelity GGUF quant, close to the official int8-convrot checkpoint in size. Not gated. Requires the ComfyUI-GGUF custom node to load. Place in models/checkpoints/.
Download LTX-2.5-Distilled-Q8_0.gguf
Direct HuggingFace download. 23.60 GB · Free.
No 24GB GPU? Try LTX-2.5-Distilled-Q8_0.gguf online — free generation included
Skip the 23.60 GB download and ComfyUI setup. Generate a 6-second video using this exact model in your browser, ~30 seconds.
Will this run on my GPU?
Minimum: 24GB VRAM. Headroom up to: 32GB.
How to use LTX-2.5-Distilled-Q8_0.gguf
- Download the file from HuggingFace.
- Place it in ComfyUI/models/checkpoints/ inside your ComfyUI directory.
- Restart ComfyUI (or refresh the model list from the menu).
- Load a compatible workflow — see below.
See the LTX 2.5 ComfyUI setup guide for the full file list and install order.
Don't want to run this locally? Try LTX-2.5-Distilled-Q8_0.gguf online with a free generation — no GPU, no install, ~30 seconds per clip.
Common issues
ComfyUI doesn't see the file after I downloaded it▼
Make sure the file is in ComfyUI/models/checkpoints/ (not a subfolder). Restart ComfyUI fully — the menu refresh sometimes misses new files. Filename must match exactly: LTX-2.5-Distilled-Q8_0.gguf.
CUDA out of memory error when loading the model▼
LTX-2.5-Distilled-Q8_0.gguf needs ~24GB VRAM minimum. If you're hitting OOM: • Enable Sequential Offloading in ComfyUI settings • Lower the resolution (768×512 instead of 1280×704) — both dimensions must be divisible by 32 • Reduce frame count (65 frames instead of 161) — must be 8n+1 • Use a smaller variant — see Related models below.
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