Repository

awesome-ltx2

A curated list of models, text encoders, and tools for the LTX-2 video generation suite. LTX-2: A New Chapter in Generative AI Prompting Guide for LTX-2 LTX-2 in ComfyUI Chattable · License unknown · Maintenance unknown

License
Unknown
Ver
Name
Model
Quant
LTX-2.3
Q2_K

Specs

  • VerName
  • VerName
  • ModelQuant
  • LTX-2.3Q2_K
  • LTX-2.3Q3_K_M
  • LTX-2.3Q3_K_S
  • LTX-2.3Q4_K_M
  • LTX-2.3Q4_K_S
  • LTX-2.3Q5_K_M
  • LTX-2.3Q5_K_S
  • LTX-2.3Q6_K
  • LTX-2.3Q8_0
  • ModelQuant
  • LTX-2-devQ2_K
  • LTX-2-devQ3_K_M
  • LTX-2-devQ3_K_S
  • LTX-2-devQ4_K_M
  • LTX-2-devQ4_K_S
  • LTX-2-devQ5_K_M
  • LTX-2-devQ5_K_S
  • LTX-2-devQ6_K
  • LTX-2-devQ8_0
  • ModelQuant
  • ltx-2.3-22bBF16
  • ltx-2.3-22bF16
  • ltx-2.3-22bQ2_K
  • ltx-2.3-22bQ3_K_M
  • ltx-2.3-22bQ3_K_S
  • ltx-2.3-22bQ4_0
  • ltx-2.3-22bQ4_1
  • ltx-2.3-22bQ4_K_M
  • ltx-2.3-22bQ4_K_S
  • ltx-2.3-22bQ5_0
  • ltx-2.3-22bQ5_1
  • ltx-2.3-22bQ5_K_M
  • ltx-2.3-22bQ5_K_S
  • ltx-2.3-22bQ6_K
  • ltx-2.3-22bQ8_0
  • ModelQuant
  • ltx-2-19b-devBF16

README

Awesome LTX-2

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

Intro

Models

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

Checkpoints

Ver Name Precision Size Download
2.3 ltx-2.3-22b dev bf16 46.1 GB Lightricks
2.3 ltx-2.3-22b dev fp8 29.1 GB Lightricks
2.3 ltx-2.3-22b distilled bf16 46.1 GB Lightricks
2.3 ltx-2.3-22b dev fp8 29.9 GB drbaph
2.3 ltx-2.3-22b distilled fp8 29.9 GB drbaph
2 ltx-2-19b dev bf16 43.3 GB Lightricks
2 ltx-2-19b dev fp8 27.1 GB Lightricks
2 ltx-2-19b dev fp4 20 GB Lightricks
2 ltx-2-19b distilled bf16 43.3 GB Lightricks
2 ltx-2-19b distilled fp8 27.1 GB Lightricks
2 ltx-2-19b distilled nvfp4 20 GB szwagros

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 fp8_e5m2 27.1 GB Lightricks

Distilled LoRA

Ver Rank Precision Size Download
2.3 384 bf16 7.61 GB Lightricks
2.3 208 bf16 4.97 GB drbaph
2.3 159 bf16 3.83 GB drbaph
2.3 105 bf16 2.59 GB Kijai
2 384 bf16 7.67 GB Lightricks
2 242 bf16 4.88 GB Lightricks
2 175 bf16 3.58 GB Lightricks
2 175 fp8 1.79 GB Lightricks

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 Lightricks
2.3 spatial-upscaler x1.5 1.0 1.09 GB Lightricks
2 spatial-upscaler x2 1.0 1.05 GB Lightricks

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 Lightricks
2 temporal-upscaler x2 1.0 262 MB Lightricks

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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 Q2_K 12.4 GB distilled
LTX-2.3 Q3_K_M 14.7 GB distilled
LTX-2.3 Q3_K_S 14 GB distilled
LTX-2.3 Q4_K_M 17.8 GB distilled
LTX-2.3 Q4_K_S 16.7 GB distilled
LTX-2.3 Q5_K_M 19.4 GB distilled
LTX-2.3 Q5_K_S 18.5 GB distilled
LTX-2.3 Q6_K 21 GB distilled
LTX-2.3 Q8_0 25.5 GB distilled

QuantStack LTX-2

Model Quant Size Download
LTX-2-dev Q2_K 8.03 GB QuantStack
LTX-2-dev Q3_K_M 10.3 GB QuantStack
LTX-2-dev Q3_K_S 9.57 GB QuantStack
LTX-2-dev Q4_K_M 13.4 GB QuantStack
LTX-2-dev Q4_K_S 12.3 GB QuantStack
LTX-2-dev Q5_K_M 15 GB QuantStack
LTX-2-dev Q5_K_S 14.2 GB QuantStack
LTX-2-dev Q6_K 16.6 GB QuantStack
LTX-2-dev Q8_0 21.1 GB QuantStack

Unsloth

Unsloth LTX-2.3 GGUF

Model Quant Size Download
ltx-2.3-22b BF16 38 GB dev ┊ distilled
ltx-2.3-22b F16 38 GB dev ┊ distilled
ltx-2.3-22b Q2_K 7.59 GB dev ┊ distilled
ltx-2.3-22b Q3_K_M 9.79 GB dev ┊ distilled
ltx-2.3-22b Q3_K_S 9.08 GB dev ┊ distilled
ltx-2.3-22b Q4_0 11.5 GB dev ┊ distilled
ltx-2.3-22b Q4_1 12.5 GB dev ┊ distilled
ltx-2.3-22b Q4_K_M 13 GB dev ┊ distilled
ltx-2.3-22b Q4_K_S 11.9 GB dev ┊ distilled
ltx-2.3-22b Q5_0 13.9 GB dev ┊ distilled
ltx-2.3-22b Q5_1 14.8 GB dev ┊ distilled
ltx-2.3-22b Q5_K_M 14.6 GB dev ┊ distilled
ltx-2.3-22b Q5_K_S 13.9 GB dev ┊ distilled
ltx-2.3-22b Q6_K 16.1 GB dev ┊ distilled
ltx-2.3-22b Q8_0 20.6 GB dev ┊ distilled

Unsloth LTX-2 GGUF

Model Quant Size Download
ltx-2-19b-dev BF16 37.8 GB Unsloth
ltx-2-19b-dev F16 37.8 GB Unsloth
ltx-2-19b-dev UD-Q2_K_L 10.1 GB Unsloth
ltx-2-19b-dev UD-Q2_K_XL 11.6 GB Unsloth
ltx-2-19b-dev Q2_K 8.1 GB Unsloth
ltx-2-19b-dev Q3_K_L 10.7 GB Unsloth
ltx-2-19b-dev Q3_K_M 10.1 GB Unsloth
ltx-2-19b-dev Q3_K_S 9.47 GB Unsloth
ltx-2-19b-dev Q4_0 11.3 GB Unsloth
ltx-2-19b-dev Q4_1 12.3 GB Unsloth
ltx-2-19b-dev Q4_K_M 12.8 GB Unsloth
ltx-2-19b-dev Q4_K_S 11.9 GB Unsloth
ltx-2-19b-dev Q5_0 13.7 GB Unsloth
ltx-2-19b-dev Q5_1 14.6 GB Unsloth
ltx-2-19b-dev Q5_K_M 14.3 GB Unsloth
ltx-2-19b-dev Q5_K_S 13.6 GB Unsloth
ltx-2-19b-dev Q6_K 16 GB Unsloth
ltx-2-19b-dev Q8_0 20.4 GB Unsloth

Vantage

Vantage AI GGUFs

Model Quant Size Download
ltx-2-19b-dev Q3_K_M 9.96 GB Download
ltx-2-19b-dev Q3_K_S 9.28 GB Download
ltx-2-19b-dev Q4_0 11.6 GB Download
ltx-2-19b-dev Q4_1 12.4 GB Download
ltx-2-19b-dev Q4_K_M 12.8 GB Download
ltx-2-19b-dev Q4_K_S 11.8 GB Download
ltx-2-19b-dev Q5_0 13.6 GB Download
ltx-2-19b-dev Q5_1 14.5 GB Download
ltx-2-19b-dev Q5_K_M 14.4 GB Download
ltx-2-19b-dev Q5_K_S 13.5 GB Download
ltx-2-19b-dev Q6_K 15.9 GB Download
ltx-2-19b-dev Q8_0 20.4 GB Download
ltx-2-19b-distilled Q3_K_M 9.96 GB Download
ltx-2-19b-distilled Q3_K_S 9.28 GB Download
ltx-2-19b-distilled Q4_0 11.6 GB Download
ltx-2-19b-distilled Q4_1 12.4 GB Download
ltx-2-19b-distilled Q4_K_M 12.8 GB Download
ltx-2-19b-distilled Q4_K_S 11.8 GB Download
ltx-2-19b-distilled Q5_0 13.6 GB Download
ltx-2-19b-distilled Q5_1 14.5 GB Download
ltx-2-19b-distilled Q5_K_M 14.4 GB Download
ltx-2-19b-distilled Q5_K_S 13.5 GB Download
ltx-2-19b-distilled Q6_K 15.9 GB Download
ltx-2-19b-distilled Q8_0 20.4 GB Download

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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 ComfyUI
gemma_3_12B_it_fpmixed 13.7 GB ComfyUI
gemma_3_12B_it_fp8_scaled 13.2 GB ComfyUI
gemma_3_12B_it_fp4_mixed 9.5 GB ComfyUI
  • 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 bf16 23.5 GB FusionCow
Gemma ablit fixed fp8 13.8 GB FusionCow

Gemma 3 12B IT Heretic

Models by DreamFast

Safetensors

Model Precision Size Download
Gemma_3_12B_it Heretic bf16 23.5 GB DreamFast
Gemma_3_12B_it Heretic fp8 12.8 GB DreamFast

GGUF

Quant Size Quality Recommendation Download
F16 22GB Lossless Reference, same as original DreamFast
Q8_0 12GB Excellent Best quality quantization DreamFast
Q6_K 9.0GB Very Good High quality, good compression DreamFast
Q5_K_M 7.9GB Good Balanced quality/size DreamFast
Q5_K_S 7.7GB Good Slightly smaller Q5 DreamFast
Q4_K_M 6.8GB Good Still useful DreamFast
Q4_K_S 6.5GB Decent Smaller Q4 variant DreamFast
Q3_K_M 5.6GB Acceptable For very low VRAM only DreamFast

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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 bf16 42 GB Kijai
2.3 ltx-2.3-22b dev fp8 23.5 GB Kijai
2.3 ltx-2.3-22b distilled bf16 42 GB Kijai
2.3 ltx-2.3-22b distilled fp8 input scaled 23.5 GB Kijai
2.3 ltx-2.3-22b distilled fp8 input scaled v2 23.2 GB Kijai
2.3 ltx-2.3-22b distilled fp8 23.5 GB Kijai
2 ltx-2-19b dev bf16 37.8 GB Kijai
2 ltx-2-19b dev fp8 21.6 GB Kijai
2 ltx-2-19b dev fp4 14.5 GB Kijai
2 ltx-2-19b distilled bf16 37.8 GB Kijai
2 ltx-2-19b distilled fp8 21.6 GB Kijai

[!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 BF16 1.45 GB Kijai ┊ Unsloth
2.3 Audio VAE BF16 365 MB Kijai ┊ Unsloth
2 Video VAE BF16 2.45 GB Kijai
2 Audio VAE BF16 218 MB Kijai

Embedding Connectors & Text Projection

Ver Name Precision Size Download
2.3 Embeddings Connectors dev bf16 2.31 GB Kijai ┊ Unsloth
2.3 Embeddings Connectors distilled bf16 2.31 GB Unsloth
2 Connector dev bf16 2.86 GB Kijai
2 Connector distilled bf16 2.86 GB Kijai

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LoRA

Enchancer, special

Styles

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Workflow & Technical Notes

Lightricks official WF:

ComfyUI official WF:

RuneXX LTX-2.3 Workflows:

Workflow
FL2V First Last Frame Injection
FML2V First Middle Last Frame Injection
I2V T2V Basic
I2V T2V Basic Custom Audio
I2V T2V Basic GGUF
T2V Basic

RuneXX LTX-2 Workflows old pre_feb2026

Workflow
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)