https://youtu.be/H5L5sO7dRu8
Creator: AI-KSK · Collection: Video 327 / six-workflow MiniMax H3 RefMod episode
Workflow file:
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
- Original audio selection:
- VAE:
- Extraction:
- Inspect node:
Upload a rights-cleared audio recording and select it in
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.
This project uses ComfyUI, MiniMax H3 weights and the upstream RefMod node pack; workflows involving
Deploy AI-KSK's H3｜RefMod免训练超级参考 image on 优云智算. 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.
Watch the complete six-workflow YouTube tutorial. 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/
Creator: AI-KSK · Collection: Video 327 / six-workflow MiniMax H3 RefMod episode
Workflow file:
03_音频RefMod_单素材制作.json · Cover file: 琥珀录音棚音频参考-3.pngMain 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
LoadAudio → MiniMaxH3RefModAudioExtract, with VAELoader providing the MiniMax H3 audio VAE. The output is inspected with MiniMaxH3RefModInspect and PreviewAudio. This graph does not use the image-folder loader from the character workflow.Exact values from this JSON
- Original audio selection:
女主.mp3 — not bundled.- VAE:
minimax_h3_audio_vae_fp32.safetensors.- Extraction:
name=Rin_Voice_01, max_seconds=8, max_tokens=0, budget_policy=truncate, concept_type=voice, subfolder=voice, save=true.- Inspect node:
preview=stored, strength=0.5; the short preview is not the source extraction duration.Suggested workflow:
Upload a rights-cleared audio recording and select it in
LoadAudio. 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 models/refmods/voice/. In Generation A it appears as voice/Rin_Voice_01 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 upstream RefMod node pack; workflows involving
VHS_ nodes require Video Helper Suite. See Comfy-Org's H3 model inventory 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.Deploy AI-KSK's H3｜RefMod免训练超级参考 image on 优云智算. 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.
Watch the complete six-workflow YouTube tutorial. 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/
Description
https://youtu.be/H5L5sO7dRu8
Creator: AI-KSK · Collection: Video 327 / six-workflow MiniMax H3 RefMod episode
Workflow file:
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
Exact values from this JSON
- Original audio selection:
- VAE:
- Extraction:
- Inspect node:
Suggested workflow:
Upload a rights-cleared audio recording and select it in
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 upstream RefMod node pack; workflows involving
Deploy AI-KSK's H3｜RefMod免训练超级参考 image on 优云智算. 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.
Watch the complete six-workflow YouTube tutorial. 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/
Creator: AI-KSK · Collection: Video 327 / six-workflow MiniMax H3 RefMod episode
Workflow file:
03_音频RefMod_单素材制作.json · Cover file: 琥珀录音棚音频参考-3.pngMain 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
LoadAudio → MiniMaxH3RefModAudioExtract, with VAELoader providing the MiniMax H3 audio VAE. The output is inspected with MiniMaxH3RefModInspect and PreviewAudio. This graph does not use the image-folder loader from the character workflow.Exact values from this JSON
- Original audio selection:
女主.mp3 — not bundled.- VAE:
minimax_h3_audio_vae_fp32.safetensors.- Extraction:
name=Rin_Voice_01, max_seconds=8, max_tokens=0, budget_policy=truncate, concept_type=voice, subfolder=voice, save=true.- Inspect node:
preview=stored, strength=0.5; the short preview is not the source extraction duration.Suggested workflow:
Upload a rights-cleared audio recording and select it in
LoadAudio. 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 models/refmods/voice/. In Generation A it appears as voice/Rin_Voice_01 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 upstream RefMod node pack; workflows involving
VHS_ nodes require Video Helper Suite. See Comfy-Org's H3 model inventory 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.Deploy AI-KSK's H3｜RefMod免训练超级参考 image on 优云智算. 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.
Watch the complete six-workflow YouTube tutorial. 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/