⬡ LTX Loader¶
Loads LTX-2.3 video+audio models with Gemma 3 dual CLIP, video/audio VAEs, and optional spatial upscaler.
Inputs¶
| Name | Type | Required | Description |
|---|---|---|---|
diff_model |
COMBO |
✅ | LTX-2.3 diffusion model (GGUF or safetensors) |
clip_gemma |
COMBO |
✅ | Gemma 3 text encoder (e.g. gemma-3-12b-it-IQ4_XS.gguf) |
clip_ltx |
COMBO |
✅ | LTX text projection / embeddings connector |
video_vae |
COMBO |
✅ | LTX Video VAE (e.g. LTX2_video_vae_bf16.safetensors) |
audio_vae |
COMBO |
✅ | LTX Audio VAE (e.g. LTX2_audio_vae_bf16.safetensors) |
latent_upscale_model |
COMBO |
❌ | Spatial upscaler 2x for dual-pass pipeline |
Outputs¶
| Name | Type | Description |
|---|---|---|
model_bundle |
UME_BUNDLE |
Complete LTX-2.3 bundle with model, dual CLIP, video VAE, audio VAE, and optional upscaler |
How It Works¶
- Diffusion Model: Loads the LTX-2.3 transformer (supports GGUF quantized and safetensors)
- Dual CLIP: Loads Gemma 3 + LTX text projection as a combined text encoder (supports GGUF for both)
- Video VAE: Loads the LTX video VAE (bf16)
- Audio VAE: Loads the LTX audio VAE with prefix remapping (
audio_vae.→autoencoder.) - Upscaler (optional): Loads the spatial 2x latent upscaler for the dual-pass pipeline
GGUF Support
Both the diffusion model and text encoders support GGUF quantized formats for reduced VRAM usage.
Dual-Pass Pipeline
When a latent upscale model is connected, the LTX Video Generator automatically uses a dual-pass pipeline: Pass 1 at half resolution → upscale 2x → Pass 2 at full resolution.
Alternative: Bundle Auto-Loader
If LTX-2.3 models are registered in model_manifest.json, you can use the ⬡ 📦 Bundle Auto-Loader instead for automatic download and loading.