Squish Anything with LTX-2 I2V and LoRA
Upload any image to apply the Squish It LoRA effect. Generate a squished animation using the LTX-2 I2V model.
Download WorkflowTry in Cloud API documentation
About
This ComfyUI workflow, titled 'Squish Anything with LTX-2 I2V and LoRA', enables users to transform static images into dynamic, squished animations. Leveraging the LTX-2 I2V model, this workflow takes an uploaded image and applies the Squish It LoRA effect to create a unique animated sequence. The workflow is designed to be intuitive, utilizing nodes such as LoadImage for importing images and SaveVideo for exporting the final animation. The b7c2d337-c38d-4c04-922b-2d638449d13e node plays a crucial role in managing the transformation process, ensuring that the animation maintains a smooth and consistent flow.
Technically, the workflow operates by first loading an image using the LoadImage node. The image is then processed through a subgraph node, which applies the Squish It LoRA effect. This effect is particularly effective at creating exaggerated, cartoon-like animations that can be both entertaining and visually striking. The LTX-2 I2V model is pivotal in this process, as it interprets the image data and generates a video sequence that reflects the squished effect. The final video is saved using the SaveVideo node, allowing for easy sharing and further editing if needed.
This workflow is particularly useful for artists and content creators looking to add a playful, animated twist to their images.
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- Reading the workflow
Runs in ComfyUI. This workflow can't run on this page. Open it in Comfy Cloud with everything loaded, or download it for your own ComfyUI.
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Inside the workflow
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Requires custom nodes
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Use this workflow from code
Generated from the workflow graph and inputs when possible; stored examples are shown otherwise. Review credentials and endpoints before running code, which may incur charges.
1 Get API key ↗
What you need
- Runs on
- Comfy Cloud
- Key
- COMFY_API_KEY
Needs a paid Cloud plan and credits.
Download API JSONAPI documentation ↗
# Python 3.10+: pip install comfy-sdk==0.4.0
import os
from comfy_sdk import Comfy
api_key = os.environ.get("COMFY_API_KEY", "").strip()
if not api_key: raise RuntimeError("Set COMFY_API_KEY")
os.environ.setdefault("COMFY_BASE_URL", "https://cloud.comfy.org")
client = Comfy(api_key=api_key)
workflow = client.workflows.from_json({
"75": {
"class_type": "SaveVideo",
"inputs": {
"filename_prefix": "video/LTX-2",
"format": "mp4",
"format.codec": "auto",
"video": [
"92:97",
0
]
},
"_meta": {
"title": "Save Video"
}
},
"98": {
"class_type": "LoadImage",
"inputs": {
"image": "puppy_with_blue_bandana.png"
},
"_meta": {
"title": "Load Image"
}
},
"92:1": {
"class_type": "CheckpointLoaderSimple",
"inputs": {
"ckpt_name": "ltx-2-19b-dev.safetensors"
},
"_meta": {
"title": "Load Checkpoint"
}
},
"92:102": {
"class_type": "PrimitiveFloat",
"inputs": {
"value": 24
},
"_meta": {
"title": "Frame Rate(float)"
}
},
"92:108": {
"class_type": "LoraLoaderModelOnly",
"inputs": {
"lora_name": "ltx-2-19b-distilled-lora-384.safetensors",
"model": [
"92:110",
0
],
"strength_model": 1
},
"_meta": {
"title": "Load LoRA"
}
},
"92:109": {
"class_type": "LoraLoaderModelOnly",
"inputs": {
"lora_name": "ltx2-squish.safetensors",
"model": [
"92:68",
0
],
"strength_model": 1
},
"_meta": {
"title": "Load LoRA"
}
},
"92:11": {
"class_type": "RandomNoise",
"inputs": {
"noise_seed": 4545545
},
"_meta": {
"title": "RandomNoise"
}
},
"92:110": {
"class_type": "LoraLoaderModelOnly",
"inputs": {
"lora_name": "ltx2-squish.safetensors",
"model": [
"92:1",
0
],
"strength_model": 1
},
"_meta": {
"title": "Load LoRA"
}
},
"92:111": {
"class_type": "ResizeImagesByLongerEdge",
"inputs": {
"images": [
"98",
0
],
"longer_edge": 1536
},
"_meta": {
"title": "Resize Images by Longer Edge (DEPRECATED)"
}
},
"92:112": {
"class_type": "LTXVPreprocess",
"inputs": {
"image": [
"92:111",
0
],
"img_compression": 33
},
"_meta": {
"title": "LTXV Preprocess"
}
},
"92:113": {
"class_type": "LTXVImgToVideoInplace",
"inputs": {
"bypass": False,
"image": [
"92:112",
0
],
"latent": [
"92:43",
0
],
"strength": 1,
"vae": [
"92:1",
2
]
},
"_meta": {
"title": "LTXVImgToVideoInplace"
}
},
"92:22": {
"class_type": "LTXVConditioning",
"inputs": {
"frame_rate": [
"92:102",
0
],
"negative": [
"92:4",
0
],
"positive": [
"92:3",
0
]
},
"_meta": {
"title": "LTXVConditioning"
}
},
"92:3": {
"class_type": "CLIPTextEncode",
"inputs": {
"clip": [
"92:60",
0
],
"text": "squish it -- a woman's voice exclaims \"I'm gonna squish this adorable little puppy... squish squish squishy\""
},
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"92:4": {
"class_type": "CLIPTextEncode",
"inputs": {
"clip": [
"92:60",
0
],
"text": "watermark, logo, channel logo, TV logo, broadcast overlay,\nUI elements, interface, HUD, subtitles, captions,\nsymbols, glyphs, letters, text, numbers,\non-screen graphics, corner marks, branding,\ntimestamp, camera overlay, app icon watermark, text, markup, logo, blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text,, missing microphone, misplaced microphone, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, smiling, laughing, exaggerated sadness, wrong gaze direction, eyes looking at camera, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, missing sniff sounds, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, missing door or shelves, missing shallow depth of field, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
},
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"92:41": {
"class_type": "SamplerCustomAdvanced",
"inputs": {
"guider": [
"92:47",
0
],
"latent_image": [
"92:56",
0
],
"noise": [
"92:11",
0
],
"sampler": [
"92:8",
0
],
"sigmas": [
"92:9",
0
]
},
"_meta": {
"title": "SamplerCustomAdvanced"
}
},
"92:43": {
"class_type": "EmptyLTXVLatentVideo",
"inputs": {
"batch_size": 1,
"height": [
"92:91",
1
],
"length": [
"92:62",
0
],
"width": [
"92:91",
0
]
},
"_meta": {
"title": "Empty LTXV Latent Video"
}
},
"92:47": {
"class_type": "CFGGuider",
"inputs": {
"cfg": 1,
"model": [
"92:108",
0
],
"negative": [
"92:22",
1
],
"positive": [
"92:22",
0
]
},
"_meta": {
"title": "CFG Guider"
}
},
"92:48": {
"class_type": "LTXVAudioVAELoader",
"inputs": {
"ckpt_name": "ltx-2-19b-dev.safetensors"
},
"_meta": {
"title": "Load LTXV Audio VAE"
}
},
"92:51": {
"class_type": "LTXVEmptyLatentAudio",
"inputs": {
"audio_vae": [
"92:48",
0
],
"batch_size": 1,
"frame_rate": [
"92:99",
0
],
"frames_number": [
"92:62",
0
]
},
"_meta": {
"title": "Empty LTXV Latent Audio"
}
},
"92:56": {
"class_type": "LTXVConcatAVLatent",
"inputs": {
"audio_latent": [
"92:51",
0
],
"video_latent": [
"92:113",
0
]
},
"_meta": {
"title": "Concat AV Latent"
}
},
"92:60": {
"class_type": "LTXAVTextEncoderLoader",
"inputs": {
"ckpt_name": "ltx-2-19b-dev.safetensors",
"device": "default",
"text_encoder": "gemma_3_12B_it.safetensors"
},
"_meta": {
"title": "Load LTXV Audio Text Encoder"
}
},
"92:62": {
"class_type": "PrimitiveInt",
"inputs": {
"value": 281
},
"_meta": {
"title": "Length"
}
},
"92:66": {
"class_type": "KSamplerSelect",
"inputs": {
"sampler_name": "euler_ancestral"
},
"_meta": {
"title": "KSamplerSelect"
}
},
"92:67": {
"class_type": "RandomNoise",
"inputs": {
"noise_seed": 0
},
"_meta": {
"title": "RandomNoise"
}
},
"92:68": {
"class_type": "LoraLoaderModelOnly",
"inputs": {
"lora_name": "ltx-2-19b-distilled-lora-384.safetensors",
"model": [
"92:1",
0
],
"strength_model": 1
},
"_meta": {
"title": "Load LoRA"
}
},
"92:70": {
"class_type": "SamplerCustomAdvanced",
"inputs": {
"guider": [
"92:82",
0
],
"latent_image": [
"92:83",
0
],
"noise": [
"92:67",
0
],
"sampler": [
"92:66",
0
],
"sigmas": [
"92:73",
0
]
},
"_meta": {
"title": "SamplerCustomAdvanced"
}
},
"92:73": {
"class_type": "ManualSigmas",
"inputs": {
"sigmas": "0.909375, 0.725, 0.421875, 0.0"
},
"_meta": {
"title": "ManualSigmas"
}
},
"92:76": {
"class_type": "LatentUpscaleModelLoader",
"inputs": {
"model_name": "ltx-2-spatial-upscaler-x2-1.0.safetensors"
},
"_meta": {
"title": "Load Latent Upscale Model"
}
},
"92:8": {
"class_type": "KSamplerSelect",
"inputs": {
"sampler_name": "euler_ancestral"
},
"_meta": {
"title": "KSamplerSelect"
}
},
"92:80": {
"class_type": "LTXVSeparateAVLatent",
"inputs": {
"av_latent": [
"92:41",
0
]
},
"_meta": {
"title": "Separate AV Latent"
}
},
"92:81": {
"class_type": "LTXVCropGuides",
"inputs": {
"latent": [
"92:80",
0
],
"negative": [
"92:22",
1
],
"positive": [
"92:22",
0
]
},
"_meta": {
"title": "LTXVCropGuides"
}
},
"92:82": {
"class_type": "CFGGuider",
"inputs": {
"cfg": 1,
"model": [
"92:109",
0
],
"negative": [
"92:81",
1
],
"positive": [
"92:81",
0
]
},
"_meta": {
"title": "CFG Guider"
}
},
"92:83": {
"class_type": "LTXVConcatAVLatent",
"inputs": {
"audio_latent": [
"92:80",
1
],
"video_latent": [
"92:84",
0
]
},
"_meta": {
"title": "Concat AV Latent"
}
},
"92:84": {
"class_type": "LTXVLatentUpsampler",
"inputs": {
"samples": [
"92:81",
2
],
"upscale_model": [
"92:76",
0
],
"vae": [
"92:1",
2
]
},
"_meta": {
"title": "spatial"
}
},
"92:89": {
"class_type": "EmptyImage",
"inputs": {
"batch_size": 1,
"color": 0,
"height": 1280,
"width": 1280
},
"_meta": {
"title": "Empty Image"
}
},
"92:9": {
"class_type": "LTXVScheduler",
"inputs": {
"base_shift": 0.95,
"latent": [
"92:56",
0
],
"max_shift": 2.05,
"steps": 12,
"stretch": True,
"terminal": 0.1
},
"_meta": {
"title": "LTXVScheduler"
}
},
"92:90": {
"class_type": "ImageScaleBy",
"inputs": {
"image": [
"92:89",
0
],
"scale_by": 0.5,
"upscale_method": "lanczos"
},
"_meta": {
"title": "Upscale Image By"
}
},
"92:91": {
"class_type": "GetImageSize",
"inputs": {
"image": [
"92:90",
0
]
},
"_meta": {
"title": "Get Image Size"
}
},
"92:94": {
"class_type": "LTXVSeparateAVLatent",
"inputs": {
"av_latent": [
"92:70",
1
]
},
"_meta": {
"title": "Separate AV Latent"
}
},
"92:96": {
"class_type": "LTXVAudioVAEDecode",
"inputs": {
"audio_vae": [
"92:48",
0
],
"samples": [
"92:94",
1
]
},
"_meta": {
"title": "LTXV Audio VAE Decode"
}
},
"92:97": {
"class_type": "CreateVideo",
"inputs": {
"audio": [
"92:96",
0
],
"bit_depth": "auto",
"codec": "none",
"color_space": "sRGB",
"fps": [
"92:102",
0
],
"images": [
"92:98",
0
]
},
"_meta": {
"title": "Create Video"
}
},
"92:98": {
"class_type": "VAEDecodeTiled",
"inputs": {
"overlap": 64,
"samples": [
"92:94",
0
],
"temporal_overlap": 8,
"temporal_size": 4096,
"tile_size": 512,
"vae": [
"92:1",
2
]
},
"_meta": {
"title": "VAE Decode (Tiled)"
}
},
"92:99": {
"class_type": "PrimitiveInt",
"inputs": {
"value": 24
},
"_meta": {
"title": "Frame Rate(int)"
}
}
})
# run() also passes api_key to the partner nodes in this workflow.
job = client.run(workflow, api_key=api_key)Questions & answers
The LoadImage node supports common image formats such as JPEG, PNG, and BMP.
Yes, the intensity of the squish effect can be adjusted within the subgraph node settings.
The default resolution is 720p, but you can use 1920x1088 if your system supports it.
No, the workflow will automatically adjust to the closest valid parameters without causing errors.