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Wan Multitalk

artokun/wan-multitalk

Build WAN MultiTalk audio-driven talking-avatar / lip-sync video workflows — MeiGen-AI MultiTalk on WAN 2.1 14B I2V via kijai WanVideoWrapper (portrait + audio → lip-synced video)

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Install

one command, takes just this skill from the repository
npx skills add https://github.com/artokun/comfyui-mcp --skill wan-multitalk

The instruction itself

7 sections, as written by the author

WAN MultiTalk — Audio-Driven Talking Avatar

Overview

MultiTalk (MeiGen-AI) drives a **still portrait's lip-sync and head motion from an

audio track**. It runs on WAN 2.1 14B Image-to-Video via kijai's

ComfyUI-WanVideoWrapper: Wav2Vec speech embeddings condition the WAN sampler so

the mouth/expression follow the speech, while the lightx2v step-distill LoRA keeps

it to a few sampling steps.

Use it for talking heads, dubbing, and single-speaker avatar clips (~10s at 480p).

It is distinct from wan-animate (pose/motion-driven character animation) — this

is *audio → lip-sync*, not reference-video motion transfer.

Pack: wan-multitalk (480p, ~10s). Higher-res/longer variants exist in the source

bundle (720p, long-context) as VRAM/duration knobs on the same graph.

Pipeline (node graph)

LoadImage (portrait) ─┐
LoadAudio ─ AudioSeparation ─ AudioCrop ─ DownloadAndLoadWav2VecModel ─ MultiTalkWav2VecEmbeds ─┐
                                                                                                 ▼
WanVideoModelLoader (WAN 2.1 14B I2V GGUF) ─ MultiTalkModelLoader ─ WanVideoLoraSelect (lightx2v)
   + LoadWanVideoT5TextEncoder (umt5) + WanVideoTextEncode + WanVideoClipVisionEncode (clip_vision_h)
   + WanVideoVAELoader ──────────────────────────────────────────────────────────────────────────┘
                                                     ▼
                       WanVideoImageToVideoMultiTalk ─ WanVideoSampler ─ WanVideoDecode ─ VHS_VideoCombine

Key nodes (all kijai WanVideoWrapper unless noted):

  • DownloadAndLoadWav2VecModel — auto-downloads the Wav2Vec speech model on first

run (no manifest entry needed).

  • MultiTalkWav2VecEmbeds — turns the (separated, cropped) speech into the

embeddings that steer the mouth/expression.

  • MultiTalkModelLoader + WanVideoImageToVideoMultiTalk — the MultiTalk head

on top of the WAN I2V model.

  • AudioSeparation — isolate the voice from music/noise before embedding (cleaner

lip-sync). AudioCrop — trim to the segment you want to animate.

  • ImageResizeKJv2 (KJNodes), VHS_VideoCombine (VideoHelperSuite) — resize +

mux to mp4.

Models

| File | Loader | Folder |

|------|--------|--------|

| Wan2.1_14b_Image_to_Video_480p_GGUF_Q8.gguf | WanVideoModelLoader | diffusion_models/ |

| WanVideo_2_1_Multitalk_14B_fp32.safetensors | MultiTalkModelLoader | diffusion_models/ |

| umt5_xxl_fp8_e4m3fn_scaled.safetensors | LoadWanVideoT5TextEncoder | text_encoders/ |

| Wan2_1_VAE_bf16.safetensors | WanVideoVAELoader | vae/ |

| clip_vision_h.safetensors | CLIPVisionLoader | clip_vision/ |

| Wan21_I2V_14B_lightx2v_cfg_step_distill_lora_rank64_fixed.safetensors | WanVideoLoraSelect | loras/ |

Sources: kijai Kijai/WanVideo_comfy, MeiGen-AI MeiGen-AI/MeiGen-MultiTalk, GGUF

city96/Wan2.1-I2V-14B-480P-gguf. See packs/wan-multitalk/manifest.yaml (some URLs

are best-effort — verify per mirror). Wav2Vec auto-downloads.

Inputs & key parameters

  • Portrait (LoadImage): front-facing, clear face, neutral-ish expression works

best. Resized by ImageResizeKJv2 to the target (480p).

  • Audio (LoadAudio): the speech track. AudioSeparation isolates the voice;

AudioCrop selects the segment (drives clip length).

  • Steps: low (the lightx2v distill LoRA is why — typically ~4–8). Raising steps

rarely helps and costs time.

  • BlockSwap (WanVideoBlockSwap): trade VRAM for speed — increase blocks swapped

to CPU on lower-VRAM cards.

VRAM tiers (from the source bundle's variants)

| Target | Approx VRAM | Lever |

|--------|-------------|-------|

| 480p 10s | ~8–12 GB | base |

| 480p low-VRAM | ~6–8.4 GB | more BlockSwap, GGUF quant, lower quality |

| 720p 10s | ~11–16 GB | higher res |

Pair with the VRAM launch-flags guidance (see troubleshooting): --use-sage-attention

+ appropriate --*vram mode; MultiTalk benefits from --reserve-vram headroom for

the Wav2Vec + VAE round-trips.

Gotchas

  • Audio must be voice-isolated for good lip-sync — skipping AudioSeparation on a

music-heavy track makes the mouth chase the wrong signal.

  • One speaker. This graph is single-speaker; multi-speaker MultiTalk needs the

multi-embed variant (not in this pack).

  • Wav2Vec first run downloads a model — the first render is slower.
  • If lips look under-driven, check the MultiTalk embeds are actually wired into

WanVideoImageToVideoMultiTalk (not bypassed), and that the audio isn't silent

after AudioCrop.

How to use it

Copy the folder

Take artokun/wan-multitalk from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.