{
  "1": {
    "class_type": "UNETLoader",
    "inputs": {
      "unet_name": "minimax_h3_ref2va_pruned_int8_convrot.safetensors",
      "weight_dtype": "default"
    }
  },
  "m0": {
    "class_type": "MiniMaxH3TurboLoRA",
    "inputs": {
      "lora_name": "minimax_h3_fl2v_lightx2v_turbo_8step_v1.0_comfy.safetensors",
      "strength": 1.0,
      "low_vram": false,
      "model": [
        "1",
        0
      ]
    },
    "_comment": "lightx2v Minimax-h3 Turbo **8step v1.0** 단독 @1.0 (2026-08-12 `t_4e40bb6cf50d` · CEO 승격 지시). 구 `ckpt850`(4step) 에서 교체 — 격자 4판 실측에서 **8step·캐시ON 이 최적**이었다: 6step·캐시OFF 대비 **80초 빠르고**(521~525s vs 601s) 오디오·화질이 같거나 낫다. ★6step·캐시ON 은 **오디오가 갈라진다**(CEO 육안 \"목소리 갈라지네\") — 속도만 보고 6step 으로 내리지 말 것."
  },
  "L2": {
    "class_type": "LoraLoaderModelOnly",
    "inputs": {
      "lora_name": "MysticXXX_MMH3-V4.safetensors",
      "strength_model": 0.4,
      "model": [
        "m0",
        0
      ]
    },
    "_comment": "Mystic XXX `MysticXXX_MMH3-V4` **0.4** — 2026-09-06 `t_0ae98911f9cb` 신설 슬롯. 체인은 `m0(터보) → L2(mystic 0.4) → m1(sage)`. ★★2026-09-10 CEO 판정으로 **realism(구 L1) 을 이 판에서 걷었다**(`t_2ac5b03c5db2`) — 사유 = *\"mystic 과 realism 이 같이 적용되면 영상 품질이 망가지더라. 각각 쓰면 괜찮은데\"*. ⇒ 종전 이 자리에 있던 *\"realism 을 빼고 그 칸을 쓰지 않았다\"* 는 **그 판정 이전의 입장**이라 걷었다 (이 필드는 실행 `workflow.json` 에까지 실리므로, 낡은 입장을 현재형으로 남기면 읽는 사람이 **누락으로 읽고 되넣는다**). ★realism 자체가 기각된 게 아니라 **Mystic 과의 동시 적용**이 기각됐다. ★값 0.4 의 근거 = 형제 `ref2va-minimax-h3-mystic-5090-1` 의 저작값과 같게 둔다(같은 파일을 두 판이 다른 강도로 쓰면 「어느 쪽이 정본인가」가 생긴다). 제작자 권장은 0.5~0.9 라 우리 값은 그 아래이고, 강도 확정은 CEO 육안 별건이다. ★끄려면 `spec_override.toggles {\"lora_2\": false}` — 그러면 러너 splice 가 `m1.model` 을 `[\"m0\", 0]` 로 되돌려 **LoRA 0장(터보만)** 체인이 된다."
  },
  "m1": {
    "class_type": "MiniMaxH3MemoryEfficientSageAttentionPatch",
    "inputs": {
      "model": [
        "L2",
        0
      ]
    }
  },
  "2": {
    "class_type": "CLIPLoader",
    "inputs": {
      "clip_name": "qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors",
      "type": "minimax",
      "device": "default"
    }
  },
  "3": {
    "class_type": "VAELoader",
    "inputs": {
      "vae_name": "minimax_h3_video_vae_fp16.safetensors"
    }
  },
  "4": {
    "class_type": "VAELoader",
    "inputs": {
      "vae_name": "minimax_h3_audio_vae_fp32.safetensors"
    }
  },
  "101": {
    "class_type": "LoadImage",
    "inputs": {
      "image": "dockaiq-input-460816-input_image-1d3f89f1-924e-4782-b9ca-989393755440.webp"
    }
  },
  "102": {
    "class_type": "LoadImage",
    "inputs": {
      "image": "dockaiq-input-460816-picture_2-ref-3shot.webp"
    }
  },
  "103": {
    "class_type": "LoadImage",
    "inputs": {
      "image": "dockaiq-input-460816-picture_3-ref-3shot.webp"
    }
  },
  "104": {
    "class_type": "LoadImage",
    "inputs": {
      "image": "dockaiq-input-460816-picture_4-ref-3shot.webp"
    }
  },
  "105": {
    "class_type": "LoadImage",
    "inputs": {
      "image": "dockaiq-input-460816-picture_5-ref-3shot.webp"
    }
  },
  "6": {
    "class_type": "MiniMaxH3ReferenceToVideo",
    "inputs": {
      "prompt": "<Picture 1> is the location; keep its layout and furnishings, surfaces clear of small objects.\n<Picture 2> is <Subject 1> — this exact person; keep the same face and hair.\n<Picture 3> is <Subject 2> — this exact person; keep the same face and hair.\n<Picture 4> is <Subject 3> — this exact person; keep the same face and hair.\n<Picture 5> is <Subject 4> — this exact person; keep the same face and hair.\n\n<Subject 1> is the woman with dark brown hair in a bun. She is seated at the side of the table, facing the viewer across the table, wearing the burgundy velvet hooded jumpsuit, barefoot, with the burgundy velvet scrunchie thick hair tie.\n<Subject 2> is the woman with lavender grey wavy bob hair. She is standing at the kitchen entrance, watching, facing the table, wearing the white scoop neck tank top, the burgundy paisley maxi skirt, the lace-up combat boots and the wool beret.\n<Subject 3> is the woman with white very long hair. She is seated at the end of the table, looking toward the doorway, wearing the black knee-length dress, the white low-top platform sneakers and the black velvet headband.\n<Subject 4> is the woman with orange wavy long hair. She is stepping out through the door gap with one hand on the door frame, facing the table, wearing the ivory ribbed knit wrap cardigan, the brown wide-leg cotton pants, the ivory cotton ankle socks, the ivory canvas sneakers, the silver minimalist hoop earrings and the silver thin chain bracelet.\n\nThe viewer, a man, says, off-screen, his mouth never in frame: <d>[Korean] 도밍 씨, 나와서 같이 앉아요.</d>\n\nThe camera is the viewer's own eyes — first-person POV from where he sits at the table, at seated eye height, looking across the table toward the doorway. <Subject 1> is seated across the table a conversational distance away, facing the camera. <Subject 2> stands at the kitchen entrance further back, facing the table. <Subject 3> sits at the end of the table, looking toward the doorway. The viewer himself never appears in frame. The camera stays fixed at his seated eye height; it does not push in on any face and does not change to a close-up.\n\nSubtle early reflections from nearby walls. The dialogue is naturally embedded in the environment rather than sounding close-miked or studio-recorded. Soft environmental ambience continuously fills the space. Very subtle natural reverberation. No artificial narration quality.\n\nNo text overlays, no subtitles, no watermark, no extra people in the background, no camera shake, no jump cuts.",
      "width": 512,
      "height": 896,
      "length": 158,
      "ref_image_size": "match",
      "clip": [
        "2",
        0
      ],
      "vae": [
        "3",
        0
      ],
      "audio_vae": [
        "4",
        0
      ],
      "ref_images.ref_image_0": [
        "101",
        0
      ],
      "ref_images.ref_image_1": [
        "102",
        0
      ],
      "ref_images.ref_image_2": [
        "103",
        0
      ],
      "ref_images.ref_image_3": [
        "104",
        0
      ],
      "ref_images.ref_image_4": [
        "105",
        0
      ]
    }
  },
  "7": {
    "class_type": "BasicGuider",
    "inputs": {
      "model": [
        "mS",
        0
      ],
      "conditioning": [
        "6",
        0
      ]
    }
  },
  "8": {
    "inputs": {
      "sampler_name": "er_sde"
    },
    "class_type": "KSamplerSelect",
    "_meta": {
      "title": "KSampler (선택)"
    }
  },
  "9": {
    "class_type": "BasicScheduler",
    "inputs": {
      "scheduler": "beta",
      "steps": 8,
      "denoise": 1.0,
      "model": [
        "mS",
        0
      ]
    }
  },
  "10": {
    "class_type": "RandomNoise",
    "inputs": {
      "noise_seed": 823584922
    }
  },
  "11": {
    "class_type": "SamplerCustomAdvanced",
    "inputs": {
      "noise": [
        "10",
        0
      ],
      "guider": [
        "7",
        0
      ],
      "sampler": [
        "8",
        0
      ],
      "sigmas": [
        "9",
        0
      ],
      "latent_image": [
        "6",
        1
      ]
    }
  },
  "12": {
    "class_type": "VAEDecode",
    "inputs": {
      "samples": [
        "11",
        0
      ],
      "vae": [
        "vb",
        0
      ]
    }
  },
  "13": {
    "class_type": "VAEDecodeAudio",
    "inputs": {
      "samples": [
        "11",
        0
      ],
      "vae": [
        "4",
        0
      ]
    }
  },
  "14": {
    "class_type": "CreateVideo",
    "inputs": {
      "fps": 24,
      "bit_depth": 8,
      "images": [
        "wm",
        0
      ],
      "audio": [
        "13",
        0
      ]
    }
  },
  "15": {
    "class_type": "SaveVideo",
    "inputs": {
      "filename_prefix": "h3_r2v_v384_j460816",
      "format": "auto",
      "video": [
        "14",
        0
      ],
      "codec": "auto"
    }
  },
  "vb": {
    "class_type": "H3VideoVAEBatchDecode",
    "inputs": {
      "vae": [
        "3",
        0
      ],
      "enabled": true
    }
  },
  "mL": {
    "inputs": {
      "head_chunks": 4,
      "model": [
        "m1",
        0
      ]
    },
    "class_type": "MiniMaxLowVRAMAttention",
    "_meta": {
      "title": "MiniMax H3 Low VRAM Attention"
    }
  },
  "mC": {
    "inputs": {
      "chunks": 2,
      "seq_threshold": 4096,
      "model": [
        "mL",
        0
      ]
    },
    "class_type": "MiniMaxChunkFeedForward",
    "_meta": {
      "title": "MiniMax H3 Chunk FeedForward"
    }
  },
  "mS": {
    "inputs": {
      "shift_video": 12.0,
      "shift_audio": 6.0,
      "model": [
        "mC",
        0
      ]
    },
    "class_type": "MiniMaxH3SigmaShift",
    "_meta": {
      "title": "ModelSamplingMiniMaxH3"
    }
  },
  "wm": {
    "inputs": {
      "images": [
        "12",
        0
      ],
      "line1": "AI",
      "line2": "yusti.net",
      "height_px": 12,
      "alpha": 0.85,
      "margin_px": 13,
      "shadow_px": 1,
      "line3": "3b024f45"
    },
    "class_type": "DockContentWatermark",
    "_meta": {
      "title": "법정 표시 워터마크 (t_88479c752c44)"
    }
  }
}