R1000/ltx-2.3-cpu
0
LTX 2.3 CPU
[LTX 2.3](https://huggingface.co/Lightricks/LTX-2.3) CPU, cond_safe distill 1.1 + Sulphur-2 merge = 10Eros.
How it works
ComfyUI runs headless with --cpu --force-fp32 --cache-none. Models are GGUF (mmap'd from disk, per-layer dequant). Workflow matches RuneXX's proven LTX 2.3 GGUF pattern: DualCLIPLoaderGGUF + SamplerCustomAdvanced + CFGGuider.
Performance
First call downloads ~20 GB of models (cached on 50 GB ephemeral disk). Verified benchmark:
Curl test
TOKEN="hf_xxx"
SPACE="https://werecooking-ltx-2-3-cpu.hf.space"
EVT=$(curl -s -X POST "$SPACE/gradio_api/call/generate" \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-d '{"data":["A woman walking through a neon-lit Tokyo alley", 2.0, 8, -1]}' \
| python -c "import sys,json;print(json.load(sys.stdin)['event_id'])")
curl -sN "$SPACE/gradio_api/call/generate/$EVT" -H "Authorization: Bearer $TOKEN"Logs
curl -N -H "Authorization: Bearer $TOKEN" "https://huggingface.co/api/spaces/WeReCooking/ltx-2.3-cpu/logs/build"
curl -N -H "Authorization: Bearer $TOKEN" "https://huggingface.co/api/spaces/WeReCooking/ltx-2.3-cpu/logs/run"Credits
- Lightricks/LTX-2.3 -- base model
- Kijai/LTX2.3_comfy -- comfy weights + tiny VAE
- city96/ComfyUI-GGUF -- GGUF loader with per-layer dequant
- TenStrip -- cond_safe distill LoRA
- unsloth -- GGUF quantization
License
Same as upstream LTX-2 Community License.
