diff --git a/comfy_extras/nodes_custom_sampler.py b/comfy_extras/nodes_custom_sampler.py
index 1e957c09b..2fbfd4139 100644
--- a/comfy_extras/nodes_custom_sampler.py
+++ b/comfy_extras/nodes_custom_sampler.py
@@ -1049,6 +1049,48 @@ class ManualSigmas(io.ComfyNode):
         sigmas = torch.FloatTensor(sigmas)
         return io.NodeOutput(sigmas)
 
+class CurveToSigmas(io.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return io.Schema(
+            node_id="CurveToSigmas",
+            display_name="Curve to Sigmas",
+            category="sampling/custom_sampling/schedulers",
+            inputs=[
+                io.Curve.Input("curve", default=[[0.0, 1.0], [1.0, 0.0]]),
+                io.Model.Input("model", optional=True),
+                io.Int.Input("steps", default=20, min=1, max=10000),
+                io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, optional=True),
+            ],
+            outputs=[io.Sigmas.Output()]
+        )
+
+    @classmethod
+    def execute(cls, curve, steps, sigma_max=14.614642, model=None) -> io.NodeOutput:
+        points = sorted(curve, key=lambda p: p[0])
+        model_sampling = model.get_model_object("model_sampling") if model is not None else None
+
+        sigmas = []
+        for i in range(steps + 1):
+            t = i / steps
+            y = points[0][1] if t < points[0][0] else points[-1][1]
+            for j in range(len(points) - 1):
+                if points[j][0] <= t <= points[j + 1][0]:
+                    x0, y0 = points[j]
+                    x1, y1 = points[j + 1]
+                    y = y0 if x1 == x0 else y0 + (y1 - y0) * (t - x0) / (x1 - x0)
+                    break
+            if model_sampling is not None:
+                sigmas.append(float(model_sampling.percent_to_sigma(1.0 - y)))
+            else:
+                sigmas.append(y * sigma_max)
+
+        sigmas[-1] = 0.0
+        return io.NodeOutput(torch.FloatTensor(sigmas))
+
+    get_sigmas = execute
+
+
 class CustomSamplersExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[io.ComfyNode]]:
@@ -1088,6 +1130,7 @@ class CustomSamplersExtension(ComfyExtension):
             AddNoise,
             SamplerCustomAdvanced,
             ManualSigmas,
+            CurveToSigmas,
         ]
 
 
diff --git a/nodes.py b/nodes.py
index 5be9b16f9..aba96a49d 100644
--- a/nodes.py
+++ b/nodes.py
@@ -2034,6 +2034,24 @@ class ImagePadForOutpaint:
         return (new_image, mask.unsqueeze(0))
 
 
+class CurveEditor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("CURVE", {"default": [[0, 0], [1, 1]]}),
+            }
+        }
+
+    RETURN_TYPES = ("CURVE",)
+    RETURN_NAMES = ("curve",)
+    FUNCTION = "execute"
+    CATEGORY = "utils"
+
+    def execute(self, curve):
+        return (curve,)
+
+
 NODE_CLASS_MAPPINGS = {
     "KSampler": KSampler,
     "CheckpointLoaderSimple": CheckpointLoaderSimple,
@@ -2102,6 +2120,7 @@ NODE_CLASS_MAPPINGS = {
     "ConditioningZeroOut": ConditioningZeroOut,
     "ConditioningSetTimestepRange": ConditioningSetTimestepRange,
     "LoraLoaderModelOnly": LoraLoaderModelOnly,
+    "CurveEditor": CurveEditor,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -2170,6 +2189,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     # _for_testing
     "VAEDecodeTiled": "VAE Decode (Tiled)",
     "VAEEncodeTiled": "VAE Encode (Tiled)",
+    "CurveEditor": "Curve Editor",
 }
 
 EXTENSION_WEB_DIRS = {}