<div data-youtube-video><iframe src="https://www.youtube.com/embed/H5L5sO7dRu8" width="640" height="360" allowfullscreen="true"></iframe></div>
https://youtu.be/H5L5sO7dRu8 
 
Creator: AI-KSK · Collection: Video 327 / six-workflow MiniMax H3 RefMod episode 
 
Workflow file: <code>03_音频RefMod_单素材制作.json</code> · Cover file: <code>琥珀录音棚音频参考-3.png</code> 
 
<h3>Main features:</h3> 
 
Instead of sending a voice recording through a visual image/video loader, this workflow encodes one audio source as a reusable H3 RefMod. It demonstrates the audio branch of the library and creates an asset that can be chosen in a later video generation graph. It is not a speaker-finetuning workflow, a text-to-speech engine or a guarantee of exact voice identity and lip sync. 
 
The connected nodes are <code>LoadAudio</code> → <code>MiniMaxH3RefModAudioExtract</code>, with <code>VAELoader</code> providing the MiniMax H3 audio VAE. The output is inspected with <code>MiniMaxH3RefModInspect</code> and <code>PreviewAudio</code>. This graph does not use the image-folder loader from the character workflow. 
 
<h3>Exact values from this JSON</h3> 
 
- Original audio selection: <code>女主.mp3</code> — not bundled. 
- VAE: <code>minimax_h3_audio_vae_fp32.safetensors</code>. 
- Extraction: <code>name=Rin_Voice_01</code>, <code>max_seconds=8</code>, <code>max_tokens=0</code>, <code>budget_policy=truncate</code>, <code>concept_type=voice</code>, <code>subfolder=voice</code>, <code>save=true</code>. 
- Inspect node: <code>preview=stored</code>, <code>strength=0.5</code>; the short preview is not the source extraction duration. 
 
<h3>Suggested workflow:</h3> 
 
Upload a rights-cleared audio recording and select it in <code>LoadAudio</code>. Prefer an isolated, clean voice sample and check the actual eight-second cap. Run the extractor, inspect the preview and locate the saved asset in <code>models/refmods/voice/</code>. In Generation A it appears as <code>voice/Rin_Voice_01</code> in the fourth loader slot. The episode transcript warns that background music in an example source influenced later generation; this graph does not automatically strip music or guarantee identity-preserving speech. 
 
<h3>Limits</h3> 
 
A source recording may carry ambience, music or other speakers into the reference representation. The preview duration does not establish the amount of audio internally retained. The microphone-and-waveform cover is a graphic depiction of an audio workflow, not a recorded voice test. 
 
<h3>Dependencies, tutorial and deployment</h3> 
 
This project uses ComfyUI, MiniMax H3 weights and the <a href="https://github.com/Luisacaotica/ComfyUI-MiniMaxH3Mod" rel="ugc">upstream RefMod node pack</a>; workflows involving <code>VHS_</code> nodes require <a href="https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite" rel="ugc">Video Helper Suite</a>. See <a href="https://huggingface.co/Comfy-Org/MiniMax-H3" rel="ugc">Comfy-Org's H3 model inventory</a> for official distribution guidance. The exact int8-convrot video VAE and Turbo 4-step LoRA named in the creator's JSON need separate availability/provenance checks. We distribute this workflow JSON and its original cover, not external checkpoints or third-party media. Respect applicable rights and licenses. 
 
<a href="https://www.compshare.cn/images/323moGjpvfeM?referral_code=A7fTQUYY9lCDFJwA6MMvoq" rel="ugc">Deploy AI-KSK's H3｜RefMod免训练超级参考 image on 优云智算</a>. Referral disclosure: the deployment link includes an AI-KSK referral code and may support the creator. Check the cloud provider's actual billing and environment before deploying. 
 
<a href="https://youtu.be/H5L5sO7dRu8" rel="ugc">Watch the complete six-workflow YouTube tutorial</a>. This project is one module in that episode. Description and settings were prepared by inspecting the source JSON and transcript, not from a new measured benchmark. 
 
Bilibili tutorial: https://www.bilibili.com/video/BV1F2nZ6SEA7/

MiniMax H3 RefMod Audio Reference

<div data-youtube-video></div>
https://youtu.be/H5L5sO7dRu8 
 
Creator: AI-KSK · Collection: Video 327 / six-workflow MiniMax H3 RefMod episode 
 
Workflow file: <code>03_音频RefMod_单素材制作.json</code> · Cover file: <code>琥珀录音棚音频参考-3.png</code> 
 
Main features: 
 
Instead of sending a voice recording through a visual image/video loader, this workflow encodes one audio source as a reusable H3 RefMod. It demonstrates the audio branch of the library and creates an asset that can be chosen in a later video generation graph. It is not a speaker-finetuning workflow, a text-to-speech engine or a guarantee of exact voice identity and lip sync. 
 
The connected nodes are <code>LoadAudio</code> → <code>MiniMaxH3RefModAudioExtract</code>, with <code>VAELoader</code> providing the MiniMax H3 audio VAE. The output is inspected with <code>MiniMaxH3RefModInspect</code> and <code>PreviewAudio</code>. This graph does not use the image-folder loader from the character workflow. 
 
Exact values from this JSON 
 
- Original audio selection: <code>女主.mp3</code> — not bundled. 
- VAE: <code>minimax_h3_audio_vae_fp32.safetensors</code>. 
- Extraction: <code>name=Rin_Voice_01</code>, <code>max_seconds=8</code>, <code>max_tokens=0</code>, <code>budget_policy=truncate</code>, <code>concept_type=voice</code>, <code>subfolder=voice</code>, <code>save=true</code>. 
- Inspect node: <code>preview=stored</code>, <code>strength=0.5</code>; the short preview is not the source extraction duration. 
 
Suggested workflow: 
 
Upload a rights-cleared audio recording and select it in <code>LoadAudio</code>. Prefer an isolated, clean voice sample and check the actual eight-second cap. Run the extractor, inspect the preview and locate the saved asset in <code>models/refmods/voice/</code>. In Generation A it appears as <code>voice/Rin_Voice_01</code> in the fourth loader slot. The episode transcript warns that background music in an example source influenced later generation; this graph does not automatically strip music or guarantee identity-preserving speech. 
 
Limits 
 
A source recording may carry ambience, music or other speakers into the reference representation. The preview duration does not establish the amount of audio internally retained. The microphone-and-waveform cover is a graphic depiction of an audio workflow, not a recorded voice test. 
 
Dependencies, tutorial and deployment 
 
This project uses ComfyUI, MiniMax H3 weights and the <a href="https://github.com/Luisacaotica/ComfyUI-MiniMaxH3Mod" rel="ugc">upstream RefMod node pack</a>; workflows involving <code>VHS_</code> nodes require <a href="https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite" rel="ugc">Video Helper Suite</a>. See <a href="https://huggingface.co/Comfy-Org/MiniMax-H3" rel="ugc">Comfy-Org's H3 model inventory</a> for official distribution guidance. The exact int8-convrot video VAE and Turbo 4-step LoRA named in the creator's JSON need separate availability/provenance checks. We distribute this workflow JSON and its original cover, not external checkpoints or third-party media. Respect applicable rights and licenses. 
 
<a href="https://www.compshare.cn/images/323moGjpvfeM?referral_code=A7fTQUYY9lCDFJwA6MMvoq" rel="ugc">Deploy AI-KSK's H3｜RefMod免训练超级参考 image on 优云智算</a>. Referral disclosure: the deployment link includes an AI-KSK referral code and may support the creator. Check the cloud provider's actual billing and environment before deploying. 
 
<a href="https://youtu.be/H5L5sO7dRu8" rel="ugc">Watch the complete six-workflow YouTube tutorial</a>. This project is one module in that episode. Description and settings were prepared by inspecting the source JSON and transcript, not from a new measured benchmark. 
 
Bilibili tutorial: https://www.bilibili.com/video/BV1F2nZ6SEA7/

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