# 1) start ComfyUI: master fd7639f4 (reports 0.43.0), torch 2.14.1+cu130, driver 580.178.04, default memory management, one GPU
python main.py --listen 127.0.0.1 --port 8291 --disable-auto-launch --output-directory <out> --temp-directory <temp> --user-directory <user>
# 2) the 4 jobs, one after the other, through the ComfyUI API (POST /prompt): cold run first, then 3 warm runs
#    the graph is workflow_api.json in this folder; per job the runner fills in the draft clip, the prompt text (prompts.json), the seed (jobs.json)
python run_regen.py --port 8291 --out <result folder> --jobs jobs.json
# 3) extra: decode only, from the saved latents (released VAE against Comfy-Org's Sol VAE)
# models in ComfyUI-models/: diffusion_models/minimax_h3_fl2va_int8_convrot.safetensors, text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors,
#   loras/minimax_h3_open_regenerate_2k_r128_comfyui_bf16_swiglu_fixed.safetensors, latent_upscale_models/minimax_h3_latent_upscaler_3d_conv_v1_bf16.safetensors,
#   vae/minimax_h3_video_vae_fp16.safetensors (main runs), vae/minimax_h3_sol_vae_fp16.safetensors (extra)
# sampling: euler, ManualSigmas 0.909375, 0.857143, 0.666667, 0.0 (3 steps), CFG 1 (BasicGuider), LoRA strength 1.0, seed 1766580932 (repeat jobs 1766580933)