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KSampler (Advanced)

sampling
KSamplerAdvanced

Example

JSON Example
{
  "class_type": "KSamplerAdvanced",
  "inputs": {
    "model": [
      "node_id",
      0
    ],
    "add_noise": "enable",
    "noise_seed": 0,
    "steps": 20,
    "cfg": 8,
    "sampler_name": "euler",
    "scheduler": "simple",
    "positive": [
      "node_id",
      0
    ],
    "negative": [
      "node_id",
      0
    ],
    "latent_image": [
      "node_id",
      0
    ],
    "start_at_step": 0,
    "end_at_step": 10000,
    "return_with_leftover_noise": "disable"
  }
}

This example shows required inputs only. Connection values like ["node_id", 0] should reference actual node IDs from your workflow.

Inputs

NameTypeStatusConstraintsDefault
modelMODELrequired--
add_noiseENUM
2 options
  • enable
  • disable
required--
noise_seedINTrequiredmin: 0, max: 1.84e+190
stepsINTrequiredmin: 1, max: 1000020
cfgFLOATrequiredmin: 0, max: 100, step: 0.18
sampler_nameENUM
44 options
  • euler
  • euler_cfg_pp
  • euler_ancestral
  • euler_ancestral_cfg_pp
  • heun
  • heunpp2
  • exp_heun_2_x0
  • exp_heun_2_x0_sde
  • 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
required--
schedulerENUM
9 options
  • simple
  • sgm_uniform
  • karras
  • exponential
  • ddim_uniform
  • beta
  • normal
  • linear_quadratic
  • kl_optimal
required--
positiveCONDITIONINGrequired--
negativeCONDITIONINGrequired--
latent_imageLATENTrequired--
start_at_stepINTrequiredmin: 0, max: 100000
end_at_stepINTrequiredmin: 0, max: 1000010000
return_with_leftover_noiseENUM
2 options
  • disable
  • enable
required--

Outputs

IndexNameTypeIs ListConnection Reference
0LATENTLATENTNo["{node_id}", 0]
How to connect to these outputs

To connect another node's input to an output from this node, use the connection reference format:

["node_id", output_index]

Where node_id is the ID of this KSamplerAdvanced node in your workflow, and output_index is the index from the table above.

Example

If this node has ID "5" in your workflow:

  • LATENT (LATENT): ["5", 0]
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