The SamplerLCM node provides an LCM (Latent Consistency Model) sampler with tunable per-step noise parameters. It allows you to control the noise applied at each sampling step, enabling fine-grained adjustment of the sampling process.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| --- | --- | --- | --- | --- |
| `s_noise` | Per-step noise multiplier at the first step. A value of 1.0 matches the model's training noise scale. (default: 1.0) | FLOAT | Yes | 0.0 to 64.0 (step: 0.01) |
| `s_noise_end` | Per-step noise multiplier at the last step. Set equal to `s_noise` for a constant noise schedule. (default: 1.0) | FLOAT | Yes | 0.0 to 64.0 (step: 0.01) |
| `noise_clip_std` | Clamps the per-step noise to within +/- N standard deviations. A value of 0 disables clamping. (default: 0.0) | FLOAT | Yes | 0.0 to 10.0 (step: 0.01) |

## Outputs

| Output Name | Description | Data Type |
| --- | --- | --- |
| `SAMPLER` | The configured LCM sampler object, ready to be used in a sampling workflow. | SAMPLER |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerLCM/en.md)

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