LTX-2: Image to Video
Transform static images into dynamic videos with LTX-2 Pro. Generate cinematic video sequences with natural motion, synchronized audio, and support for up to 4K resolution at 50fps.
Download WorkflowTry in Cloud API documentation
00:00
Inside the workflow
A read-only preview of the source template. Open it in Cloud to explore the nodes and make changes.
Loading the graph
Open full-size workflow preview- Output
- Video
- Author
- ComfyUI
Call this model from your code
The request below uses the same prepared graph and settings as the Playground. Each submission can start a paid run; do not automatically retry a submission whose outcome is unknown.
1 Get API key ↗
What you need
- Runs on
- Comfy Cloud
- Key
- COMFY_API_KEY
- Your files
- Uploaded by the code from their urls
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_2.0_i2v",
"format": "auto",
"format.codec": "auto",
"video": [
"92:97",
0
]
},
"_meta": {
"title": "Save Video"
}
},
"98": {
"class_type": "LoadImage",
"inputs": {
"image": "UPLOADED_image_FILENAME"
},
"_meta": {
"title": "Load Image"
}
},
"102": {
"class_type": "ResizeImageMaskNode",
"inputs": {
"input": [
"98",
0
],
"resize_type": "scale dimensions",
"resize_type.crop": "center",
"resize_type.height": 720,
"resize_type.width": 1280,
"scale_method": "lanczos"
},
"_meta": {
"title": "Resize Image/Mask"
}
},
"92:1": {
"class_type": "CheckpointLoaderSimple",
"inputs": {
"ckpt_name": "ltx-2-19b-dev-fp8.safetensors"
},
"_meta": {
"title": "Load Checkpoint"
}
},
"92:105": {
"class_type": "GetImageSize",
"inputs": {
"image": [
"102",
0
]
},
"_meta": {
"title": "Get Image Size"
}
},
"92:106": {
"class_type": "ResizeImagesByLongerEdge",
"inputs": {
"images": [
"102",
0
],
"longer_edge": 1536
},
"_meta": {
"title": "Resize Images by Longer Edge (DEPRECATED)"
}
},
"92:107": {
"class_type": "LTXVImgToVideoInplace",
"inputs": {
"bypass": False,
"image": [
"92:99",
0
],
"latent": [
"92:43",
0
],
"strength": 1,
"vae": [
"92:1",
2
]
},
"_meta": {
"title": "LTXVImgToVideoInplace"
}
},
"92:108": {
"class_type": "LTXVImgToVideoInplace",
"inputs": {
"bypass": False,
"image": [
"92:99",
0
],
"latent": [
"92:84",
0
],
"strength": 1,
"vae": [
"92:1",
2
]
},
"_meta": {
"title": "LTXVImgToVideoInplace"
}
},
"92:11": {
"class_type": "RandomNoise",
"inputs": {
"noise_seed": 10
},
"_meta": {
"title": "RandomNoise"
}
},
"92:22": {
"class_type": "LTXVConditioning",
"inputs": {
"frame_rate": 25,
"negative": [
"92:4",
0
],
"positive": [
"92:3",
0
]
},
"_meta": {
"title": "LTXVConditioning"
}
},
"92:3": {
"class_type": "CLIPTextEncode",
"inputs": {
"clip": [
"92:60",
0
],
"text": "Morning in the sunlit piazza. The street violinist draws a long, sweeping bow stroke and launches into a fast, joyful folk melody, fingers dancing along the fingerboard, body swaying with the rhythm, eyes closed in a broad smile. Fine rosin dust sparkles in the low sunlight with each stroke. Behind him a flock of pigeons bursts up from the warm tiles and wheels across the clear sky over the arched colonnade. The camera starts low and wide, then slowly circles around him from left to right at waist height, keeping the violin and both hands in view, ending on a closer three-quarter view of his face. Sound: bright solo violin playing a lively tune, the flutter of pigeon wings, distant seagulls and soft footsteps echoing across the stone square."
},
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"92:4": {
"class_type": "CLIPTextEncode",
"inputs": {
"clip": [
"92:60",
0
],
"text": "blurry, low quality, still frame, frames, watermark, overlay, titles, has blurbox, has subtitles"
},
"_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": 4,
"model": [
"92:1",
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-fp8.safetensors"
},
"_meta": {
"title": "Load LTXV Audio VAE"
}
},
"92:51": {
"class_type": "LTXVEmptyLatentAudio",
"inputs": {
"audio_vae": [
"92:48",
0
],
"batch_size": 1,
"frame_rate": 25,
"frames_number": [
"92:62",
0
]
},
"_meta": {
"title": "Empty LTXV Latent Audio"
}
},
"92:56": {
"class_type": "LTXVConcatAVLatent",
"inputs": {
"audio_latent": [
"92:51",
0
],
"video_latent": [
"92:107",
0
]
},
"_meta": {
"title": "Concat AV Latent"
}
},
"92:60": {
"class_type": "LTXAVTextEncoderLoader",
"inputs": {
"ckpt_name": "ltx-2-19b-dev-fp8.safetensors",
"device": "default",
"text_encoder": "gemma_3_12B_it_fp4_mixed.safetensors"
},
"_meta": {
"title": "Load LTXV Audio Text Encoder"
}
},
"92:62": {
"class_type": "PrimitiveInt",
"inputs": {
"value": 121
},
"_meta": {
"title": "Length"
}
},
"92:66": {
"class_type": "KSamplerSelect",
"inputs": {
"sampler_name": "gradient_estimation"
},
"_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"
},
"_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": [
"92:68",
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": [
"92:108",
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": [
"92:105",
1
],
"width": [
"92:105",
0
]
},
"_meta": {
"title": "Empty Image"
}
},
"92:9": {
"class_type": "LTXVScheduler",
"inputs": {
"base_shift": 0.95,
"latent": [
"92:56",
0
],
"max_shift": 2.05,
"steps": 20,
"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"
}
},
"92:95": {
"class_type": "VAEDecode",
"inputs": {
"samples": [
"92:94",
0
],
"vae": [
"92:1",
2
]
},
"_meta": {
"title": "VAE Decode"
}
},
"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": 25,
"images": [
"92:95",
0
]
},
"_meta": {
"title": "Create Video"
}
},
"92:99": {
"class_type": "LTXVPreprocess",
"inputs": {
"image": [
"92:106",
0
],
"img_compression": 33
},
"_meta": {
"title": "LTXV Preprocess"
}
}
})
workflow.set_input("98", "image", client.assets.from_url("https://comfy.org/catalog-media/6710d2a9-cf4b-46d3-ada6-d54cebaebec1/dbc88c9d-a8c8-46d0-9ffb-2d84ad53b810"))
# run() also passes api_key to the partner nodes in this workflow.
job = client.run(workflow, api_key=api_key)
for output in job.get_outputs("75"):
output.to_file(output.name)Try an example
About this workflow
The LTX-2: Image to Video workflow is designed to transform static images into dynamic videos, seamlessly integrating audio and video generation. This workflow utilizes the LTX-2 model from Lightricks, known for its ability to produce expressive lip synchronization and natural motion, ensuring that the generated videos appear realistic and engaging.
The workflow leverages several nodes, including SaveVideo for output, LoadImage for importing static images, and ResizeImageMaskNode for adjusting image dimensions to fit video requirements. The b7c2d337-c38d-4c04-922b-2d638449d13e node is crucial for processing and synchronizing audio with video, enhancing the overall multimedia experience.
By using this workflow, users can efficiently create high-quality videos from images, making it a powerful tool for content creators looking to add dynamic elements to their projects.
Questions & answers
Ensure your image dimensions are divisible by 64 for optimal video compatibility.
The b7c2d337-c38d-4c04-922b-2d638449d13e node handles audio synchronization, so ensure it's correctly configured in your workflow.
Yes, you can use 1920x1088 resolution if your hardware supports it, but ensure all parameters meet the divisibility requirements.
The workflow will silently adjust to the nearest valid parameters without causing errors, ensuring smooth operation.