<- Docs Home . Model Catalog . HTTP API . Troubleshooting

LTX-2.3 LoRA Inference with Diffusers (AI Toolkit-trained)

API model id: ltx2.3 URL slug: ltx2.3

This page documents the reference Diffusers inference pipeline for ltx2.3 (LTX-2.3). It inherits all behavior from the LTX-2 pipeline with the following differences:

• Base model: dg845/LTX-2.3-Diffusers (community-converted diffusers format; official Lightricks repo Lightricks/LTX-2.3 is single-file checkpoint only)
• Vocoder: Uses LTX2VocoderWithBWE (Bandwidth Extension) for improved audio quality

Quick facts

Field	Value
Pipeline	src/pipelines/ltx2.py (LTX23Pipeline)
Base checkpoint	dg845/LTX-2.3-Diffusers
Defaults	sample_steps=25, guidance_scale=4.0, seed=42
Resolution snapping	Floors width/height to a multiple of 32
Control image	Optional (ctrl_img switches to I2V)
Video	Yes (num_frames=41, fps=24 by default)
LoRA scale behavior	Same as LTX-2: LoRA converted (AI Toolkit -> diffusers) and applied via set_adapters (hotswap).
Needs AI Toolkit	Optional (recommended for LoRA conversion helpers via AI_TOOLKIT_PATH)

Minimal API request

{
  "model": "ltx2.3",
  "trigger_word": "sks",
  "prompts": [
    {
      "prompt": "[trigger] a photo of a person",
      "width": 768,
      "height": 512,
      "seed": 42,
      "sample_steps": 25,
      "guidance_scale": 4.0,
      "neg": "",
      "num_frames": 41,
      "fps": 24
    }
  ],
  "loras": [
    {
      "path": "my_lora_job/my_lora.safetensors",
      "network_multiplier": 1.0
    }
  ]
}

Pipeline behavior

All behavior is inherited from the LTX-2 pipeline. See the LTX-2 documentation for details on:

• T2V and I2V modes
• LoRA loading and conversion
• Preview-matching notes
• Debugging mismatch

Related

• LTX-2