<div data-youtube-video><iframe width="640" height="480" allowfullscreen="true" autoplay="false" disablekbcontrols="false" enableiframeapi="false" endtime="0" ivloadpolicy="0" loop="false" modestbranding="false" origin playlist src="https://www.youtube.com/embed/4Obats2LZMY?rel=1" start="0"></iframe></div>This workflow is designed for LTX 2.3 four-image reference video generation, allowing creators to build a continuous cinematic video from multiple visual references instead of relying on a single image or a text prompt alone. Its main purpose is to use four reference images as visual anchors for scene design, character appearance, product details, atmosphere, and motion continuity, then generate a coherent LTX 2.3 video with stronger control over identity, environment, and visual logic.The workflow uses LTX 2.3 Dev-Dare merged distilled components as the main video generation backbone, together with Gemma 3 text encoding, LTX audio / video latent routing, LTX video VAE decoding, and a custom sampler structure. It also includes enhancement routes such as LTX2.3 Crisp Enhance and VBVR I2V-style LoRA support, making it more suitable for controlled image-to-video generation where visual consistency matters.The key feature is the multi-reference guide structure. Four images can be loaded and processed separately, then resized and prepared through ImageResizeKJv2 and LTXVPreprocess. These references are injected into the generation process through LTXVAddGuideMulti. This gives the model more than one visual source to follow. One image can define the main subject, another can define the product, another can provide the scene or lighting mood, and another can guide the final visual style or atmosphere.The workflow also uses PromptRelayEncodeTimeline, which is important for video control. Instead of writing only one static prompt, the workflow can describe the video as a time-based sequence. The global prompt defines the overall scene, subject, atmosphere, and visual rules, while local prompts describe what happens in different time segments. This makes the final video more cinematic and less random, because the model receives both a stable visual concept and a clear temporal direction.In the uploaded setup, the workflow is structured around a polished beauty product showcase. The prompt describes a young adult East Asian woman presenting a blue skincare serum bottle in a clean studio or cinematic environment, with controlled camera movement, soft light, product visibility, and stable character performance. This shows the intended strength of the workflow: it is not only for abstract animation, but also for commercial-style video generation, product demonstration, AI influencer clips, fashion previews, and short-form advertising content.The workflow includes multiple sampling and refinement stages, manual sigma control, NAG enhancement, latent upscaling, tiled VAE decoding, and final video export. These sections help improve detail, reduce drift, and make the output more usable for publishing. The final result can be exported as a video through the video combine route, making it ready for RunningHub demos, Civitai previews, YouTube showcases, and Bilibili publishing.In short, this is a practical four-image reference LTX 2.3 video workflow for creators who want stronger visual control, better reference fusion, and more stable cinematic video output. If you want to see how the four reference images are connected, how PromptRelay controls the timeline, and how the final video is generated, watch the full tutorial from the YouTube link above.⚙️ Try the Workflow Online👉 Workflow: <a target="_blank" rel="ugc" href="https://www.runninghub.ai/post/2052698989765644290?inviteCode=rh-v1111">https://www.runninghub.ai/post/2052698989765644290?inviteCode=rh-v1111</a>Open the link above to run the workflow directly online and view the generation results in real time.If the results meet your expectations, you can also deploy it locally for further customization.🎁 Fan Benefits: Register now to get 1000 points, plus 100 daily login points — enjoy 4090-level performance and 48 GB of powerful compute!📺 Bilibili Updates (Mainland China &amp; Asia-Pacific)If you are in Mainland China or the Asia-Pacific region, you can watch the video below for workflow demos and a detailed creative breakdown.📺 Bilibili Video: <a target="_blank" rel="ugc" href="https://www.bilibili.com/video/BV1DERQBeEm1/">https://www.bilibili.com/video/BV1DERQBeEm1/</a>I will continue updating model resources on Quark Drive:👉 <a target="_blank" rel="ugc" href="https://pan.quark.cn/s/20c6f6f8d87b">https://pan.quark.cn/s/20c6f6f8d87b</a>These resources are mainly prepared for local users, making creation and learning more convenient.⚙️ 在线体验工作流👉 工作流： <a target="_blank" rel="ugc" href="https://www.runninghub.ai/post/2052698989765644290?inviteCode=rh-v1111">https://www.runninghub.ai/post/2052698989765644290?inviteCode=rh-v1111</a>打开上方链接即可直接运行该工作流，实时查看生成效果。如果觉得效果理想，你也可以在本地进行自定义部署。🎁 粉丝福利： 注册即送 1000 积分，每日登录 100 积分，畅玩 4090 体验 48 G 超级性能！📺 Bilibili 更新（中国大陆及南亚太地区）如果你在中国大陆或南亚太地区，可以通过下方视频查看该工作流的实测效果与构思讲解。📺 B站视频： <a target="_blank" rel="ugc" href="https://www.bilibili.com/video/BV1DERQBeEm1/">https://www.bilibili.com/video/BV1DERQBeEm1/</a>我会在 夸克网盘 持续更新模型资源：👉 <a target="_blank" rel="ugc" href="https://pan.quark.cn/s/20c6f6f8d87b">https://pan.quark.cn/s/20c6f6f8d87b</a>这些资源主要面向本地用户，方便进行创作与学习。

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