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This R2V workflow combines multiple image references with MiniMax H3 to build a short cinematic video. Different images can define the character, prop, environment, or visual language while the prompt controls how those references are staged over time.
The workflow uses the MiniMax H3 local ComfyUI graph with the connected model, VAE, encoder, sampler, resolution, and video output chain shown in the JSON.
Main features:
- MiniMax H3 FL2VA diffusion model with connected video VAE and Qwen3-VL encoder
- MiniMaxH3ReferenceToVideo node for multi-image reference conditioning
- Reference images can define identity, props, environment, and scene details
- Connected 16:9 widescreen resolution route at the 0.4 megapixel setting
- 20-step simple scheduler with res_multistep sampling
- Prompt-controlled shot order, camera movement, action, and audio direction
- Direct SaveVideo output for the generated result
Suggested workflow:
Assign each reference image a clear role in the prompt, such as character, object, or environment. Avoid giving two images conflicting identity instructions. Keep the first test short, verify the reference composition, then expand the action and camera description after the visual roles are stable.
⚡ RunningHub Workflow
Try the workflow online right now - no installation required.
👉 Workflow: https://www.runninghub.ai/post/2084544634998575105?inviteCode=rh-v1111
If the results meet your expectations, you can later deploy it locally for customization.
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📵 Bilibili Updates (Mainland China & Asia-Pacific)
If you're in the Asia-Pacific region, you can watch the video below to see the workflow demonstration and creative breakdown.
📵 Bilibili Video: https://www.bilibili.com/video/BV1MrMk69Ejk/
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⚡ 打开下方链接即可在线体验，无需安装。
👉 工作流：https://www.runninghub.ai/post/2084544634998575105?inviteCode=rh-v1111
如果你觉得效果理想，也可以在本地进行自定义部署。
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📵 B站视频（中国大陆及亚洲地区）
如果你在中国大陆或亚洲地区，可以通过下面的视频查看工作流的实测效果与创作思路。
📵 B站视频：https://www.bilibili.com/video/BV1MrMk69Ejk/
我会在夸克网盘持续更新模型资源：
👉 https://pan.quark.cn/s/07bdc81784ce