ComfyUI Node: Wan MoE KSampler
Category
sampling
Inputs
model_high_noise MODEL
model_low_noise MODEL
boundary FLOAT
seed INT
steps INT
cfg_high_noise FLOAT
cfg_low_noise FLOAT
sampler_name
- euler
- euler_cfg_pp
- euler_ancestral
- euler_ancestral_cfg_pp
- heun
- heunpp2
- dpm_2
- dpm_2_ancestral
- lms
- dpm_fast
- dpm_adaptive
- dpmpp_2s_ancestral
- dpmpp_2s_ancestral_cfg_pp
- dpmpp_sde
- dpmpp_sde_gpu
- dpmpp_2m
- dpmpp_2m_cfg_pp
- dpmpp_2m_sde
- dpmpp_2m_sde_gpu
- dpmpp_2m_sde_heun
- dpmpp_2m_sde_heun_gpu
- dpmpp_3m_sde
- dpmpp_3m_sde_gpu
- ddpm
- lcm
- ipndm
- ipndm_v
- deis
- res_multistep
- res_multistep_cfg_pp
- res_multistep_ancestral
- res_multistep_ancestral_cfg_pp
- gradient_estimation
- gradient_estimation_cfg_pp
- er_sde
- seeds_2
- seeds_3
- sa_solver
- sa_solver_pece
- ddim
- uni_pc
- uni_pc_bh2
scheduler
- simple
- sgm_uniform
- karras
- exponential
- ddim_uniform
- beta
- normal
- linear_quadratic
- kl_optimal
sigma_shift FLOAT
positive CONDITIONING
negative CONDITIONING
latent_image LATENT
denoise FLOAT
Outputs
LATENT
Extension: KSampler for Wan 2.2 MoE for ComfyUI
These nodes are made to support 'Mixture of Expert' Flow models with the architecture of Wan2.2 A14B (With a high noise expert and low noise expert). Instead of guessing the denoising step at which to swap from tyhe high noise model to the low noise model, this node automatically chanage to the low noise model when we reach the diffusion timestep at which the signal to noise ratio is supposed to be 1:1.
Authored by stduhpf
Run ComfyUI workflows in the Cloud!
No downloads or installs are required. Pay only for active GPU usage, not idle time. No complex setups and dependency issues
Learn more