Awesome LTX-2

A curated list of models, text encoders, and tools for the LTX-2 video generation suite.

Intro

• LTX-2: A New Chapter in Generative AI

• ComfyUI official blogpost

• Prompting Guide for LTX-2

• »» LTX-2 in ComfyUI Chattable KB

▓ Apps & Tools

LTX2.3-Multifunctional

LTX2.3-Multifunctional is a desktop-optimized version of LTX that lowers GPU requirements and simplifies usage. It integrates all features including image-to-video, text-to-video, start/end frames, lip-sync, video enhancement, and image generation into a single application.

Key Features:

• Lower GPU Requirements: Only needs 24GB VRAM (vs 32GB for standard desktop version)
• All-in-One Interface: No complex ComfyUI workflows or error-prone nodes
• Features: T2V, I2V, start/end frames, lip-sync, video enhancement, image generation, LoRA support
• Multi-Frame Insertion: Two modes for generating long videos
• Easy Setup: No third-party software required, just install LTX desktop

Downloads & Resources:

• HuggingFace | GitHub | ComfyUI Node | Tutorial

▓ Models

LTX-2 models are available in various formats including full weights, transformers-only, and GGUF quantizations for efficient inference.

▣ Checkpoints

• Lightricks/LTX-2 - Official repository.
• Lightricks/LTX-2.3 - Official repository (latest version).
• Drbaph - Quantization

Ver	Name	Precision	Size	Download
2.3	ltx-2.3-22b dev		46.1 GB
2.3	ltx-2.3-22b dev		29.1 GB
2.3	ltx-2.3-22b dev		29.9 GB
2.3	ltx-2.3-22b dev		29.1 GB
2.3	ltx-2.3-22b dev		21.7 GB
2.3	ltx-2.3-22b dev		29.1 GB
2.3	ltx-2.3-22b distilled		46.1 GB
2.3	ltx-2.3-22b distilled		29.5 GB
2.3	ltx-2.3-22b distilled		29.9 GB
2.3	ltx-2.3-22b distilled		29.1 GB
2.3	ltx-2.3-22b distilled		17.6 GB
2.3	ltx-2.3-22b distilled		29.7 GB
2.3	ltx-2.3-22b distilled 1.1		46.1 GB
2	ltx-2-19b dev		43.3 GB
2	ltx-2-19b dev		27.1 GB
2	ltx-2-19b dev		20 GB
2	ltx-2-19b distilled		43.3 GB
2	ltx-2-19b distilled		27.1 GB
2	ltx-2-19b distilled		20 GB

Quantized to fp8_e5m2 to support older Triton with older Pytorch on 30 series GPUs. For WangGP in Pinokio

Ver	Name	Precision	Size	Download
2	ltx-2-19b dev		27.1 GB

Distilled LoRA

Ver	Rank	Precision	Size	Download
2.3	384		7.61 GB	┊
2.3	208		4.97 GB
2.3	159		3.83 GB
2.3	111		2.74 GB
2.3	105		2.59 GB
2	384		7.67 GB
2	242		4.88 GB
2	175		3.58 GB
2	175		1.79 GB

Spatial Upscaler

Required for current two-stage pipeline implementations in this repository. Download to COMFYUI_ROOT_FOLDER/models/latent_upscale_models folder.

Ver	Name	Size	Download
2.3	spatial-upscaler x2 1.0	996 MB
2.3	spatial-upscaler x1.5 1.0	1.09 GB
2	spatial-upscaler x2 1.0	1.05 GB

Temporal Upscaler

Required for current two-stage pipeline implementations in this repository. Download to COMFYUI_ROOT_FOLDER/models/latent_upscale_models folder.

Ver	Name	Size	Download
2.3	temporal-upscaler x2 1.0	262 MB
2	temporal-upscaler x2 1.0	262 MB

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▣ GGUF Quantized Models

These models are optimized for lower memory usage. Note that in ComfyUI, these are typically loaded as transformer-only models.

QuantStack

QuantStack LTX-2.3

Model	Quant	Size	Download
ltx-2.3-22b		12.4 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		14.7 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		14 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		17.8 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		16.7 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		19.4 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		18.5 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		21 GB	dev ┊ distilled ┊ distilled-1.1
ltx-2.3-22b		25.5 GB	dev ┊ distilled ┊ distilled-1.1

QuantStack LTX-2

Model	Quant	Size	Download
LTX-2-dev		8.03 GB
LTX-2-dev		10.3 GB
LTX-2-dev		9.57 GB
LTX-2-dev		13.4 GB
LTX-2-dev		12.3 GB
LTX-2-dev		15 GB
LTX-2-dev		14.2 GB
LTX-2-dev		16.6 GB
LTX-2-dev		21.1 GB

Unsloth

Unsloth LTX-2.3 GGUF

Model	Quant	Size	Download
ltx-2.3-22b		42 GB	dev ┊ distilled
ltx-2.3-22b		42 GB	dev ┊ distilled
ltx-2.3-22b		8.28 GB	dev ┊ distilled
ltx-2.3-22b		10.8 GB	dev ┊ distilled
ltx-2.3-22b		9.95 GB	dev ┊ distilled
ltx-2.3-22b		12.7 GB	dev ┊ distilled
ltx-2.3-22b		13.8 GB	dev ┊ distilled
ltx-2.3-22b		14.3 GB	dev ┊ distilled
ltx-2.3-22b		13.1 GB	dev ┊ distilled
ltx-2.3-22b		15.3 GB	dev ┊ distilled
ltx-2.3-22b		16.3 GB	dev ┊ distilled
ltx-2.3-22b		16.1 GB	dev ┊ distilled
ltx-2.3-22b		15.2 GB	dev ┊ distilled
ltx-2.3-22b		17.8 GB	dev ┊ distilled
ltx-2.3-22b		22.8 GB	dev ┊ distilled
ltx-2.3-22b		8.98 GB	dev ┊ distilled
ltx-2.3-22b		11.8 GB	dev ┊ distilled
ltx-2.3-22b		10.5 GB	dev ┊ distilled
ltx-2.3-22b		15.1 GB	dev ┊ distilled
ltx-2.3-22b		13.7 GB	dev ┊ distilled
ltx-2.3-22b		17.1 GB	dev ┊ distilled
ltx-2.3-22b		15.8 GB	dev ┊ distilled

Unsloth LTX-2 GGUF

Model	Quant	Size	Download
ltx-2-19b-dev		37.8 GB
ltx-2-19b-dev		37.8 GB
ltx-2-19b-dev		10.1 GB
ltx-2-19b-dev		11.6 GB
ltx-2-19b-dev		8.1 GB
ltx-2-19b-dev		10.7 GB
ltx-2-19b-dev		10.1 GB
ltx-2-19b-dev		9.47 GB
ltx-2-19b-dev		11.3 GB
ltx-2-19b-dev		12.3 GB
ltx-2-19b-dev		12.8 GB
ltx-2-19b-dev		11.9 GB
ltx-2-19b-dev		13.7 GB
ltx-2-19b-dev		14.6 GB
ltx-2-19b-dev		14.3 GB
ltx-2-19b-dev		13.6 GB
ltx-2-19b-dev		16 GB
ltx-2-19b-dev		20.4 GB

Vantage

Vantage AI GGUFs

Model	Quant	Size	Download
ltx-2-19b-dev		9.96 GB
ltx-2-19b-dev		9.28 GB
ltx-2-19b-dev		11.6 GB
ltx-2-19b-dev		12.4 GB
ltx-2-19b-dev		12.8 GB
ltx-2-19b-dev		11.8 GB
ltx-2-19b-dev		13.6 GB
ltx-2-19b-dev		14.5 GB
ltx-2-19b-dev		14.4 GB
ltx-2-19b-dev		13.5 GB
ltx-2-19b-dev		15.9 GB
ltx-2-19b-dev		20.4 GB
ltx-2-19b-distilled		9.96 GB
ltx-2-19b-distilled		9.28 GB
ltx-2-19b-distilled		11.6 GB
ltx-2-19b-distilled		12.4 GB
ltx-2-19b-distilled		12.8 GB
ltx-2-19b-distilled		11.8 GB
ltx-2-19b-distilled		13.6 GB
ltx-2-19b-distilled		14.5 GB
ltx-2-19b-distilled		14.4 GB
ltx-2-19b-distilled		13.5 GB
ltx-2-19b-distilled		15.9 GB
ltx-2-19b-distilled		20.4 GB

Special Quantization: PolarQuant Q5

LTX-2.3 (22B) — PolarQuant Q5 is a bit-packed quantization method using Hadamard-Rotated Lloyd-Max Quantization. It achieves optimal Gaussian weight quantization via Hadamard rotation, delivering near-lossless quality with significant size reduction.

Specification

Specification	Value
Parameters	22B
Transformer Blocks	48
Hidden Dimension	4096
Layers Quantized	1,347 (of 5,947 total tensors)

Compression Statistics:

Component	Original Size	PQ5 Packed	Reduction
Transformer (1,347 layers)	37 GB	4.6 GB	-88%
VAE + Skip (4,600 layers)	9.1 GB	9.1 GB	BF16 kept
Upscalers	1.3 GB	1.3 GB	BF16 kept
Total	46.2 GB	15 GB	-68%

Quality Metrics:

• Cosine Similarity: 0.9986 (near-lossless)
• Download Size: 15 GB
• Beats torchao INT4 on perplexity (PPL)

Hardware Requirements:

GPU	VRAM	Status
A100 (80 GB)	80 GB	Full speed
A100 (40 GB)	40 GB	Recommended
RTX 4090 (24 GB)	24 GB	With offloading

Key Features:

• Mixed precision approach: transformer heavily quantized (-88%) while VAE remains BF16
• 5-bit bit-packed representation (Q5)
• 50-65% smaller than original with zero quality loss
• One-command setup with easy generation wrapper

Model	Size	Download
LTX-2.3-22B-PolarQuant-Q5	15 GB

Installation: pip install safetensors huggingface_hub scipy ArXiv Reference: 2603.29078

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▓ Text Encoders

LTX-2 requires Gemma-3-12b variants. LTX-2.3 uses text projection layers.

▣ Comfy-Org Optimized Encoders

Official and optimized versions for ComfyUI.

Model Name	Size	Download
gemma_3_12B_it	24.4 GB
gemma_3_12B_it_fpmixed	13.7 GB
gemma_3_12B_it_fp8_scaled	13.2 GB
gemma_3_12B_it_fp4_mixed	9.5 GB
gemma_3_12B_it-int8tensormixed	13.2 GB
gemma_3_12B_it-int8tensormixed	13.2 GB
text_projection_fp8	1.16 GB

• gemma_3_12B_it_fpmixed: Experimental quant. Should be better than the fp8 scaled
• gemma_3_12B_it_fp4_mixed: 90% fp4 layers

▣ Gemma-3-12b Abliterated

Why Choose Abliterated Encoders?

Standard Gemma models often incorporate safety alignment that "sanitizes" or weakens specific concepts within prompt embeddings. Even when the model doesn't explicitly refuse a request, this internal filtering can dilute creative intent. For LTX-2 video generation, using a standard encoder often results in:

• Reduced Prompt Adherence: Key stylistic or descriptive terms may be ignored or weakened.
• Visual Softening: Visual intensity and fine details are often "muted" to fit generic safety profiles.
• Concept Dilution: Complex or niche creative requests are subtly altered, leading to less faithful representations of your vision.

Abliteration bypasses these restrictive alignment layers, allowing the encoder to translate your prompts into embeddings with maximum fidelity. This ensures LTX-2 receives the most accurate and un-filtered instructions possible.

Gemma-3-12b-Abliterated

Fixed versions of the abliterated Gemma-3-12b-it model by FusionCow, modified specifically for compatibility with LTX-2. The original model

Model	Precision	Size	Download
Gemma ablit fixed		23.5 GB
Gemma ablit fixed		13.8 GB

Gemma 3 12B IT Heretic

Models by DreamFast

Safetensors

Model	Precision	Size	Download
Gemma_3_12B_it Heretic		23.5 GB
Gemma_3_12B_it Heretic		12.8 GB

GGUF

Quant	Size	Quality	Recommendation	Download
	22GB	Lossless	Reference, same as original
	12GB	Excellent	Best quality quantization
	9.0GB	Very Good	High quality, good compression
	7.9GB	Good	Balanced quality/size
	7.7GB	Good	Slightly smaller Q5
	6.8GB	Good	Still useful
	6.5GB	Decent	Smaller Q4 variant
	5.6GB	Acceptable	For very low VRAM only

Sikaworld1990 Gemma-3-12b Abliterated

NVFP4 quantization variants by Sikaworld1990 optimized for Blackwell GPUs.

Model	Precision	Size	Download
Gemma-3-12b QAT Abliterated FP4		12.1 GB
Gemma-3-12b QAT Abliterated FP4		8.91 GB
Gemma-3-12b HereticX Abliterated		15 GB
Gemma-3-12b High-Fidelity Abliterated		14.1 GB

• FP4-HF: High-fidelity mixed precision calibration
• FP4-Pure: Pure FP4 quantization for maximum compression
• HereticX: Uncensored variant with maximum prompt fidelity
• High-Fidelity: Optimized for quality with better detail preservation

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▓ Separated Components

Separated LTX2 checkpoint by Kijai and Kijai for LTX-2.3. For alternative way to load the models in Comfy.

▣ Diffusion Models (Transformer Only)

Ver	Name	Precision	Size	Download
2.3	ltx-2.3-22b dev		42 GB
2.3	ltx-2.3-22b dev		23.5 GB
2.3	ltx-2.3-22b dev		25 GB
2.3	ltx-2.3-22b distilled		42 GB
2.3	ltx-2.3-22b distilled		23.5 GB
2.3	ltx-2.3-22b distilled v2		23.2 GB
2.3	ltx-2.3-22b distilled		23.5 GB
2.3	ltx-2.3-22b distilled (experimental)		24.1 GB
2.3	ltx-2.3-22b distilled 1.1		42 GB
2.3	ltx-2.3-22b distilled 1.1		25.2 GB
2.3	ltx-2.3-22b distilled 1.1 (experimental)		24.1 GB
2	ltx-2-19b dev		37.8 GB
2	ltx-2-19b dev		21.6 GB
2	ltx-2-19b dev		14.5 GB
2	ltx-2-19b distilled		37.8 GB
2	ltx-2-19b distilled		21.6 GB

Note

input_scaled additionally have activation scaling, and are set to run with fp8 matmuls on supported hardware (roughly 40xx and later Nvidia GPUs).

▣ VAE (Video & Audio)

Ver	Component	Precision	Size	Download
2.3	Video VAE		1.45 GB	┊
2.3	Audio VAE		365 MB	┊
2	Video VAE		2.45 GB
2	Audio VAE		218 MB

▣ Embedding Connectors & Text Projection

Ver	Name	Precision	Size	Download
2.3	Embeddings Connectors dev		2.31 GB	┊
2.3	Embeddings Connectors distilled		2.31 GB
2	Connector dev		2.86 GB
2	Connector distilled		2.86 GB

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▓ LoRA

▣ Enchancer, special

• LTX-2.3-IC-LoRA-Colorizer by DoctorDiffusion (331 MB) - Colorize black and white videos
• Arnold Style by bionicman69 - Arnold Style LoRA for LTX 2.3. Get to the choppa!
• JUST-DUB-IT
• Best-Face-Swap-Video
• Image-to-Video Adapter LoRA
  • Original by MachineDelusions
  • siraxe variant - Stripped audio layers + rank64 compressed (2.62 GB, 655 MB rank64 bf16)
• Lightricks LTX-2.3
  • Union Control - Unified IC-LoRA combining Canny + Depth + Pose control signals for multi-signal video generation conditioning
  • Motion Track Control - Guides object motion using sparse point trajectories via colored spline overlays on reference videos
• vrgamedevgirl84
  • ClayMationStyle - Clay animation style LoRA for LTX-2.3
  • Enhancer1 - Video enhancement LoRA
  • Enhancer2 - Second video enhancement LoRA
• oumoumad
  • LTX-2 IC-LoRA-Ungrade - Removes color grading and contrast from footage, returning neutral ungraded appearance
  • LTX-2.3 IC-LoRA-Ungrade - LTX-2.3 version of color grading removal IC-LoRA
  • IC-LoRA-Outpaint - Extends video canvas by generating new content in black regions (letterbox areas), filling with temporally consistent content
• Cseti
  • IC-LoRA-Cameraman v1 - Transfers camera movements (zoom, pan, tilt, orbit) from reference video to generated output
• 100percentrobot
  • Audio-Reactive LORA - Generates audio-reactive videos with motion synchronized to musical elements (beats, rhythm)
• LiconStudio
  • VBVR-lora-I2V - Enhances video generation for complex reasoning tasks including multi-object interactions, physical causality, and spatial relationships
• lopho
  • Gantz O v1.0.0 - Movie-style LoRA (654 MB, 10000 steps)
• o-8-o
  • Skin-Hair - Refines skin texture and hair rendering, reduces plastic skin artifacts, improves specular highlights (353 MB)
• Nightfury16
  • Staging IC-lora 512 - Staging IC-LoRA for video composition control (512 latent scale)
• siraxe
  • MergeGreen IC-lora - Maintains motion at start/end frames, use middle frames with RGB 0,191,0 (75% green fill) in IC-LoRA workflow
  • TTM IC-lora - Makes cutouts cartoony and adds cartoony characters to video scenes, based on the TTM approach (use with Img To Video bypass + Add Video IC-LoRA Guide node)
• Lightricks LTX-2
  • Canny Control - Edge detection control for structural guidance
  • Depth Control - Depth map conditioning for 3D spatial control
  • Detailer - Enhances fine details and textures in generated videos
  • Pose Control - Human pose estimation control for motion guidance

▣ Styles

• LTX-2-19b-LoRA-SPROUT
• Hydraulic press
• Cakeify
• Big Anime Breasts
• Clay Stop Motion
• Eat
• POP! Inflatable Animation - Comically inflate and pop cartoon/anime characters into confetti and fabric scraps (I2V focused)
• Anime2Half-Real - Converts anime-style content to a half-realistic aesthetic while maintaining visual consistency with the original anime reference (4500 steps, rank64)
• Outfit Switch
• Handheld run
• Atomic Explosion
• Squish
• IC luminance map
• Yoshiaki Kawajiri Retro Anime - LoRA trained on Yoshiaki Kawajiri's distinctive retro anime art style
• DonaldTrump
• WHATUSEE
• Squish – One Hand Only
• Black Venom
• HERO CAM
• Animatediff V1
• PUSH TO GLASS
• Object POV
• Group Photo
• EarthZoomOut
• Lightricks
  • Camera Control: dolly-in
  • Camera Control: dolly-left
  • Camera Control: dolly-out
  • Camera Control: dolly-right
  • Camera Control: jib-down
  • Camera Control: jib-up
  • Camera Control: static
  • Union-Control

▣ Special

• Wan2.1 VAE Adapter
  • Latent space adapter for converting between LTX-2 and Wan2.1 VAE representations
  • latent_adapter_final.pt (447 MB)

▣ ID-LoRA (Identity-Driven In-Context LoRA)

ID-LoRA is a method that enables identity-preserving audio-video generation in a single model. It jointly generates a subject's appearance and voice, letting a text prompt, a reference image, and a short audio clip govern both modalities together. Built on top of LTX-2.3 (22B), it is the first method to personalize visual appearance and voice within a single generative pass.

Unlike cascaded pipelines that treat audio and video separately, ID-LoRA operates in a unified latent space where a single text prompt can simultaneously dictate the scene's visual content, environmental acoustics, and speaking style—while preserving the subject's vocal identity and visual likeness.

Key Features:

• Text prompt controls the scene and content
• Reference image preserves the subject's visual likeness
• Short audio clip preserves the subject's vocal identity
• Single unified generation pass for both appearance and voice

Available LoRAs for LTX-2.3:

LoRA	LoRA Rank	Size	Download
ID-LoRA-TalkVid-3K	128	1.1 GB	┊
ID-LoRA-CelebVHQ-3K	128	1.1 GB	┊

Resources:

• Project Page | GitHub | Paper (arXiv: 2603.10256)

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▓ Workflow & Technical Notes

❖ Lightricks

LTX-2.3:

• ICLoRA Motion Track Control
• Union Control
• Single Stage
• Two Stage

LTX-2:

• Text to Video Full
• Text to Video Distilled
• Image to Video Full
• Image to Video Distilled
• ICLoRA
• Video to Video
• Video to Video Detailer

❖ ComfyUI

• Text-to-video
• Text-to-video Distilled (faster, 8 steps)
• Image-to-video
• Image-to-video Distilled (faster, 8 steps)
• Depth control
• Canny control
• Pose control

❖ RuneXX

RuneXX LTX-2.3 Workflows:

• I2V T2V Basic
• I2V T2V Basic GGUF
• I2V T2V Dev Full-Steps
• I2V T2V Simple Single Pass
• T2V Basic
• T2V Simple Single Pass

Talking-Avatar-TTS:

• I2V T2V Talking Avatar (Qwen-TTS)
• I2V T2V Talking Avatar (Fish-Audio-Pro)
• I2V T2V Talking Avatar (OmniVoice-TTS)

Video-2-Video:

• V2V Just Talk Prompt Lipsynced Voice
• V2V Just Talk Prompt Lipsynced Voice Sam3
• V2V Dub It lip-synced dubbing multilanguage
• V2V Extend Any Video
• V2V Expand Any Video IC-Lora-Outpaint
• V2V Foley Add Sound To Any Video
• V2V ReTake recreate any section of any video

Custom-Audio:

• I2V T2V Basic ID-Lora Reference Audio
• I2V T2V Dev Custom Audio
• I2V T2V Basic Custom Audio

First-Last-Frame:

• FLF2V First Last Frame
• FLF2V First Last Frame Custom Audio
• FLF2V First Last Frame Transition LoRA
• FML2V First Middle Last Frame Guider
• FML2V First Middle Last Frame Injection
• FML2V Guider Custom Audio

Long-Video-Experimental:

• I2V T2V Long Video Custom Audio Loop
• I2V T2V Long Video Custom Audio
• I2V T2V Long Video Custom Audio singlepass loop

3-Pass-Experimental:

• I2V T2V Experimental 3-pass 1.5x Upscaler
• I2V T2V DEV Experimental 3-Pass

Control-reference:

• I2V TV2V Transfer Camera Movements IC-Cameraman LoRA
• I2V TV2V Transfer Body Movements IC-Union-Control-lora DWPose
• I2V TV2V Transfer Body Movements IC-Union-Control-lora SDPose

Music-Video-Creator:

• I2V T2V Music-Video-Creator Multi-Scene Custom Audio
• I2V T2V Music-Video-Creator Multi-Scene Custom Audio Low RAM

Helper-Workflows:

• AceStep-XL Create Music From a Prompt
• Flux-Klein Transform Firstframe
• Qwen-Image Transform Firstframe Next Scene or Different Angle LoRA

Other-examples:

• I2V T2V Basic Custom Audio with Gemma-API

RuneXX LTX-2 Workflows old pre_feb2026

• First Last Frame (guide node)
• First Last Frame (in-place node)
• First Middle Last Frame (guide node)
• I2V Basic (GGUF)
• I2V Basic
• I2V IC-Control (pose)
• I2V Simple First Middle Last Frame (1-pass K-Sampler)
• I2V Talking Avatar (voice clone Qwen-TTS)
• I2V and T2V (beta test sampler previews)
• I2V and T2V Basic (Custom Audio)
• I2V and T2V IC-Control (All-In-One Pose Canny Depth)
• I2V and T2V Simple (1-pass K-Sampler)
• I2V and T2V Simple (1-pass)
• T2V Basic (GGUF)
• T2V Basic (low vram)
• T2V Basic
• T2V Talking Avatar (voice clone Qwen-TTS)
• V2A Foley (add sound to any video)
• V2V (extend any video)
• V2V Head Swap Experimental (BFS lora)
• V2V Just Dub It (experimental)(translate speech auto dubbing)
• V2V Just Dub It (with voice clone)(auto dubbing translation)(experimental)