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VideoFlow (LTX 2.3, Wan 2.2/2.1) - I2V image-to-video img2vid workflow

Type

Workflows

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1,956

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Reviews

Published

Mar 15, 2026

Base Model

LTXV 2.3

Hash

AutoV2
E542D20BCE
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ai839's Avatar

ai839

Update 2026-03-15: LTX 2.3 I2V workflow added

VideoFlow LTX 2.3 distilled I2V v1.0

This workflow provides an easy-to-use image-to-video solution for LTX 2.3, designed to work seamlessly with the distilled LoRA model. It focuses on high-quality, realistic output, with the first-stage scheduler's sigma values finely optimized for best performance.

Subgraphs are used to keep the main workflow streamlined and easy to navigate. A live preview is displayed during generation, allowing you to monitor progress and stop the process early if desired. Additionally, the first-stage video can be decoded for quick previewing. This feature lets you watch a lower-resolution version of the final video and cancel immediately if the result doesn’t meet expectations.

As the distilled LoRA already delivers impressive quality in the first stage, you can skip the second stage entirely if your hardware has limited performance. An optional color-correction node is included to compensate for LTX’s tendency to introduce subtle color and lighting shifts, ensuring consistent visual quality.


Update 2025-08-24: Wan 2.2 I2V workflow added

VideoFlow Wan 2.2 I2V v1.0

VideoFlow is now fully optimized for Wan 2.2. It supports resolutions from 480p up to 720p, with the option to upscale smoothly to 1440p at 32fps. The process is accelerated by integrating Lightning LoRA during the final two-thirds of the generation steps, ensuring faster results without compromising quality. Importantly, Lightning LoRA does not influence the initial generation steps, preserving natural and fluid movements throughout the video. SageAttention with Triton is supported but not required. Instructions on how to set up and use the workflow are included within the workflow itself.


VideoFlow Wan 2.1 I2V v1.0

This image-to-video workflow is designed to generate smooth, realistic videos at 32 fps with a strong emphasis on fast, high-resolution output. At least 16 GB of VRAM is recommended for optimal performance. For additional speed improvements, you may also install SageAttention and Triton, though these are optional.

It's fast 🚀!

Sample videos were rendered at 768 × 1152 resolution and 16 fps, consisting of 81 frames, each video taking about 6 minutes to generate. The upscaling and frame interpolation to 1536 × 2304 resolution and 32 fps took approximately another 6 minutes on an RTX 4080 with 16 GB VRAM. Lower resolutions render even faster.

Key configuration for the sample videos:

  • Video model: Wan2.1 SkyReels V2 I2V 14B 720P

  • LoRA: Lightx2v

  • Steps: 4

  • Sampler: dpmpp_sde_gpu

  • Scheduler: beta

💡Comprehensive usage details and instructions are provided within the workflow itself.

Sample images for input were created with my PhotoFlow workflow.

The download of the workflow contains all sample videos, including the input image with its own workflow, the initial generated video and its upscaled counterpart, allowing for convenient side-by-side comparison.

Leave a 👍 if you like the workflow 🙂.