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Video: https://youtu.be/AqyyLY_ajTQ

In this video, we dive deep into the latest capabilities of LTX2 with ComfyUI, showing you how to fully control AI-generated video using your own custom audio input. Unlike basic image-to-video setups, we’re using video-to-video generation with LTX2 LoRA models and ControlNet—paired with native audio conditioning via the LTX Audio VAE Encode node. This allows for synchronized facial expressions, natural lip movements, and dynamic motion that matches your voice or music track, all generated locally without extra plugins.

This tutorial is perfect for AI creators, digital artists, indie filmmakers, and YouTubers who want to produce high-quality, expressive AI avatars or stylized music videos using open-source tools. Whether you're experimenting with talking head avatars, animated narrations, or full-blown AI music videos, this workflow gives you precise control over timing, motion, and emotional expression—something static image-to-video simply can’t deliver reliably.

Why does this matter? Because LTX2 in ComfyUI now supports true audio-aware video generation, letting you go beyond generic prompts and create content that reacts to your audio. With features like audio latent encoding, frame-count syncing, Stage 1/Stage 2 sampling, and distilled LoRA detailers, you get studio-level polish without cloud costs or proprietary software. If you’ve been waiting for a local, open-source alternative to commercial AI video tools—this is it.

Resources:

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LTX-2 Model Card

https://huggingface.co/Lightricks/LTX-2

ComfyUI-LTXVideo Custom Nodes

https://github.com/Lightricks/ComfyUI-LTXVideo

LTXV2 Models include GGUF

https://huggingface.co/Kijai/LTXV2_comfy

🅛🅣🅧 Gemma 3 Model Loader (follow the Text Encoder from LTX Team)

https://github.com/Lightricks/ComfyUI-LTXVideo?tab=readme-ov-file#required-models

Gemma 3 (For high VRam) https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-unquantized

Gemma-3-12b-it-bnb-4bit (For low VRam) https://huggingface.co/unsloth/gemma-3-12b-it-bnb-4bit

Comfy-Org/ltx-2 - gemma_3_12B_it.safetensors

https://huggingface.co/Comfy-Org/ltx-2/tree/main/split_files/text_encoders

ComfyUI-VoxCPMTTS

https://github.com/1038lab/ComfyUI-VoxCPMTTS

ComfyUI-VoxCPMTTS

https://github.com/1038lab/ComfyUI-VoxCPMTTS

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Have Fun!

Files

ComfyUI LTX2 + Custom Audio = Perfect Lip Sync & Motion! You Can Make Your Own MV!

In this video, we dive deep into the latest capabilities of LTX2 with ComfyUI, showing you how to fully control AI-generated video using your own custom audio input. Unlike basic image-to-video setups, we’re using video-to-video generation with LTX2 LoRA models and ControlNet—paired with native audio conditioning via the LTX Audio VAE Encode node. This allows for synchronized facial expressions, natural lip movements, and dynamic motion that matches your voice or music track, all generated locally without extra plugins. This tutorial is perfect for AI creators, digital artists, indie filmmakers, and YouTubers who want to produce high-quality, expressive AI avatars or stylized music videos using open-source tools. Whether you're experimenting with talking head avatars, animated narrations, or full-blown AI music videos, this workflow gives you precise control over timing, motion, and emotional expression—something static image-to-video simply can’t deliver reliably. Why does this matter? Because LTX2 in ComfyUI now supports true audio-aware video generation, letting you go beyond generic prompts and create content that reacts to your audio. With features like audio latent encoding, frame-count syncing, Stage 1/Stage 2 sampling, and distilled LoRA detailers, you get studio-level polish without cloud costs or proprietary software. If you’ve been waiting for a local, open-source alternative to commercial AI video tools—this is it. LTX-2 Model Card https://huggingface.co/Lightricks/LTX-2 ComfyUI-LTXVideo Custom Nodes https://github.com/Lightricks/ComfyUI-LTXVideo LTXV2 Models include GGUF https://huggingface.co/Kijai/LTXV2_comfy 🅛🅣🅧 Gemma 3 Model Loader (follow the Text Encoder from LTX Team) https://github.com/Lightricks/ComfyUI-LTXVideo?tab=readme-ov-file#required-models Gemma 3 (For high VRam) https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-unquantized Gemma-3-12b-it-bnb-4bit (For low VRam) https://huggingface.co/unsloth/gemma-3-12b-it-bnb-4bit Comfy-Org/ltx-2 - gemma_3_12B_it.safetensors https://huggingface.co/Comfy-Org/ltx-2/tree/main/split_files/text_encoders ComfyUI-VoxCPMTTS https://github.com/1038lab/ComfyUI-VoxCPMTTS LTX2 V2V Controlnet + Custom Audio Workflow: https://www.patreon.com/posts/148361592?utm_source=youtube&utm_medium=video&utm_campaign=20260116 -------------------------------------------------------------------------------------------------------------------------------- Local Workstation GPU : https://amzn.to/3XfXsAO -------------------------------------------------------------------------------------------------------------------------------- If You Like tutorial like this, You Can Support Our Work In Patreon: https://www.patreon.com/c/aifuturetech

Comments

moelle

Hey man, its me again, the annoying paying supporter of you 😅🙈 - just a question. I'm still kinda disappointed with the ltx2 i2v results - regarding the visual quality. I just tried again SVI 2.0 pro and its creating way more consistent results but lacks good motion. Did you by chance do an svi 2.0 pro workflow thats using openpose? Or is that even supported by SVI? I'd like to test ltx videos - use the sound and pose data of it on a SVI process to use its images but the motion and sound of ltx. Sorry for being a little pain in .. with all my comments 🙈😅