ltx-2.3-22b-distilled-fp8.safetensors
LTX 2.3 Distilled FP8 (Official)
Official FP8 distilled model from Lightricks. 8 steps, CFG=1.
Released 2026-03-16 · Source: Lightricks/LTX-2.3-fp8 (HuggingFace) — First-party FP8 distilled release. Same v1.0 weights as the non-FP8 distilled, quantized to FP8. Lightricks did not publish a v1.1 FP8 in this repo — use the Kijai mirror for v1.1.
Download ltx-2.3-22b-distilled-fp8.safetensors
Direct HuggingFace download. 29.5 GB · Free.
No 16GB GPU? Try ltx-2.3-22b-distilled-fp8.safetensors online — free generation included
Skip the 29.5 GB download and ComfyUI setup. Generate a 6-second video using this exact model in your browser, ~30 seconds.
Technical details
Lightricks' first-party FP8 quantization of the v1.0 distilled model. Like the official dev FP8, this is a full checkpoint — transformer + VAE + text encoder integration glue — which is why the file is ~29.5 GB versus ~25 GB for a transformer-only quant.
The weights here are the v1.0 distilled checkpoint quantized to FP8. That means 8-step sampling with CFG=1, fast inference, and the v1.0 quality profile — not the v1.1 improvements that landed later in April 2026.
FP8 hardware (RTX 40-series Ada or newer) is required. On RTX 30-series the matmul falls back to a slow path; switch to the MXFP8 block-32 variant from Kijai if that's your GPU.
When to choose ltx-2.3-22b-distilled-fp8.safetensors
Use this when you need official Lightricks distilled weights at FP8 size — for example, building a reproducible reference pipeline or matching the exact outputs documented in Lightricks' v1.0 distilled release notes.
For most ComfyUI users, ltx-2.3-22b-distilled-1.1_transformer_only_fp8_scaled.safetensors (Kijai, v1.1) is a better default: newer weights, smaller file, and the filename every current workflow JSON references.
If you need v1.0 specifically (for reproducibility or comparison), this is the cleanest source — official, signed, in the same repo as the official dev FP8.
Will this run on my GPU?
Minimum: 16GB VRAM. Headroom up to: 24GB.
⚠ FP8 scaled matmul requires RTX 40-series or newer (Ada Lovelace architecture). RTX 30xx cannot run this format — use the MXFP8 block-32 or BF16 variant instead.
Recommendation: Official FP8 distilled from Lightricks. Alternative to Kijai's FP8.
How to use ltx-2.3-22b-distilled-fp8.safetensors
- 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.
Compatible official workflows:
- LTX-2.3_T2V_I2V_Single_Stage_Distilled_Full.json— T2V / I2V Single Stage Distilled
- LTX-2.3_T2V_I2V_Two_Stage_Distilled.json— T2V / I2V Two Stage Distilled
- LTX-2.3_ICLoRA_Union_Control_Distilled.json— ICLoRA Union Control Distilled
- LTX-2.3_ICLoRA_Motion_Track_Distilled.json— ICLoRA Motion Track Distilled
- LTX-2.3_ICLoRA_HDR_Distilled.json— ICLoRA HDR Distilled
Don't want to run this locally? Try ltx-2.3-22b-distilled-fp8.safetensors online with a free generation — no GPU, no install, ~30 seconds per clip.
Common issues
Output quality is lower than the Kijai v1.1 FP8 file at the same settings▼
This file is v1.0 weights, not v1.1. v1.1 is a meaningfully better release for fast motion and consistency. Fix: Switch to ltx-2.3-22b-distilled-1.1_transformer_only_fp8_scaled.safetensors if you don't need v1.0 specifically for reproducibility.
Workflow expects a 'transformer_only' file but downloaded this full checkpoint▼
Most community workflow JSONs load the transformer, VAE, and text encoder separately and expect Kijai-style transformer-only files. Fix: Either rewire the workflow to load the full checkpoint (single LoadCheckpoint node), or download ltx-2.3-22b-distilled_transformer_only_fp8_scaled.safetensors from Kijai for the v1.0 transformer-only equivalent.
Generation is slower than expected even on a 4090▼
Activations + Gemma BF16 text encoder + VAE add up. The 29.5 GB on-disk size grows substantially during inference. Fix: Use gemma_3_12B_it_fp4_mixed.safetensors as the text encoder. Cap resolution at 768p on 16 GB cards. On 24 GB you can run 1024p comfortably.
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-2.3-22b-distilled-fp8.safetensors.
I get a CUDA error mentioning fp8 / scaled / matmul▼
FP8 scaled matmuls require an RTX 40-series GPU or newer (Ada Lovelace architecture). RTX 30-series and older cannot run FP8 weights at native precision. Use the BF16 variant instead, or the MXFP8 block-32 alternative.
CUDA out of memory error when loading the model▼
ltx-2.3-22b-distilled-fp8.safetensors needs ~16GB 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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