ComfyUI V1 → V3 Migration Guide

Migrate existing V1 nodes to the modern V3 API. V3 uses classmethods, typed inputs/outputs, and ComfyExtension registration.

Migration Checklist

Change base class to io.ComfyNode
Replace INPUT_TYPES() with define_schema() returning io.Schema
Rename execution function to execute and make it a @classmethod
Replace return tuples with io.NodeOutput(...)
Replace IS_CHANGED with fingerprint_inputs
Replace VALIDATE_INPUTS with validate_inputs
Convert check_lazy_status to @classmethod
Replace NODE_CLASS_MAPPINGS with ComfyExtension + comfy_entrypoint()
Access hidden inputs via cls.hidden instead of kwargs
Remove __init__ methods (no instance state in V3)

Side-by-Side Comparison

V1 (Before)

import torch

class ImageInvertV1:
    CATEGORY = "image"
    FUNCTION = "invert"
    RETURN_TYPES = ("IMAGE",)
    RETURN_NAMES = ("image",)
    OUTPUT_TOOLTIPS = ("The inverted image",)
    DESCRIPTION = "Inverts image colors"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": ("IMAGE",),
                "strength": ("FLOAT", {
                    "default": 1.0,
                    "min": 0.0,
                    "max": 1.0,
                    "step": 0.01,
                }),
            },
            "optional": {
                "mask": ("MASK",),
            },
            "hidden": {
                "unique_id": "UNIQUE_ID",
            },
        }

    @classmethod
    def IS_CHANGED(s, image, strength, mask=None, unique_id=None):
        return strength

    @classmethod
    def VALIDATE_INPUTS(s, image, strength, mask=None, unique_id=None):
        if strength < 0:
            return "Strength must be non-negative"
        return True

    def invert(self, image, strength, mask=None, unique_id=None):
        inverted = 1.0 - image
        result = image * (1 - strength) + inverted * strength
        if mask is not None:
            result = image * (1 - mask.unsqueeze(-1)) + result * mask.unsqueeze(-1)
        return (result,)

NODE_CLASS_MAPPINGS = {"ImageInvertV1": ImageInvertV1}
NODE_DISPLAY_NAME_MAPPINGS = {"ImageInvertV1": "Invert Image"}

V3 (After)

import torch
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io

class ImageInvertV3(io.ComfyNode):
    @classmethod
    def define_schema(cls):
        return io.Schema(
            node_id="ImageInvertV3",
            display_name="Invert Image",
            description="Inverts image colors",
            category="image",
            inputs=[
                io.Image.Input("image"),
                io.Float.Input("strength", default=1.0, min=0.0, max=1.0, step=0.01),
                io.Mask.Input("mask", optional=True),
            ],
            outputs=[
                io.Image.Output("IMAGE", tooltip="The inverted image"),
            ],
            hidden=[io.Hidden.unique_id],
        )

    @classmethod
    def fingerprint_inputs(cls, image, strength, mask=None):
        return strength

    @classmethod
    def validate_inputs(cls, image, strength, mask=None):
        if strength < 0:
            return "Strength must be non-negative"
        return True

    @classmethod
    def execute(cls, image, strength, mask=None):
        node_id = cls.hidden.unique_id  # access hidden via cls.hidden

        inverted = 1.0 - image
        result = image * (1 - strength) + inverted * strength
        if mask is not None:
            result = image * (1 - mask.unsqueeze(-1)) + result * mask.unsqueeze(-1)
        return io.NodeOutput(result)


class MyExtension(ComfyExtension):
    @override
    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return [ImageInvertV3]

async def comfy_entrypoint() -> MyExtension:
    return MyExtension()

Property Mapping

| V1 Property | V3 Equivalent | |---|---| | CATEGORY = "image" | io.Schema(category="image") | | FUNCTION = "my_func" | Always execute (fixed name) | | RETURN_TYPES = ("IMAGE",) | outputs=[io.Image.Output()] | | RETURN_NAMES = ("image",) | outputs=[io.Image.Output(display_name="image")] | | OUTPUT_TOOLTIPS = ("tip",) | outputs=[io.Image.Output(tooltip="tip")] | | OUTPUT_NODE = True | io.Schema(is_output_node=True) | | DEPRECATED = True | io.Schema(is_deprecated=True) | | EXPERIMENTAL = True | io.Schema(is_experimental=True) | | API_NODE = True | io.Schema(is_api_node=True) | | NOT_IDEMPOTENT = True | io.Schema(not_idempotent=True) | | DESCRIPTION = "..." | io.Schema(description="...") | | SEARCH_ALIASES = [...] | io.Schema(search_aliases=[...]) | | INPUT_IS_LIST = True | io.Schema(is_input_list=True) | | OUTPUT_IS_LIST = (True,) | io.Image.Output(is_output_list=True) | | DEV_ONLY = True | io.Schema(is_dev_only=True) | | ESSENTIALS_CATEGORY = "Basic" | io.Schema(essentials_category="Basic") |

Input Type Mapping

| V1 Input | V3 Input | |---|---| | ("IMAGE",) | io.Image.Input("id") | | ("MASK",) | io.Mask.Input("id") | | ("LATENT",) | io.Latent.Input("id") | | ("MODEL",) | io.Model.Input("id") | | ("CLIP",) | io.Clip.Input("id") | | ("VAE",) | io.Vae.Input("id") | | ("CONDITIONING",) | io.Conditioning.Input("id") | | ("INT", {"default": 0, ...}) | io.Int.Input("id", default=0, ...) | | ("FLOAT", {"default": 1.0, ...}) | io.Float.Input("id", default=1.0, ...) | | ("STRING", {"multiline": True}) | io.String.Input("id", multiline=True) | | ("BOOLEAN", {"default": True}) | io.Boolean.Input("id", default=True) | | (["opt1", "opt2"],) | io.Combo.Input("id", options=["opt1", "opt2"]) | | ("CONTROL_NET",) | io.ControlNet.Input("id") | | ("CLIP_VISION",) | io.ClipVision.Input("id") | | ("CLIP_VISION_OUTPUT",) | io.ClipVisionOutput.Input("id") | | ("STYLE_MODEL",) | io.StyleModel.Input("id") | | ("GLIGEN",) | io.Gligen.Input("id") | | ("UPSCALE_MODEL",) | io.UpscaleModel.Input("id") | | ("AUDIO",) | io.Audio.Input("id") | | ("VIDEO",) | io.Video.Input("id") | | ("SAMPLER",) | io.Sampler.Input("id") | | ("SIGMAS",) | io.Sigmas.Input("id") | | ("NOISE",) | io.Noise.Input("id") | | ("GUIDER",) | io.Guider.Input("id") | | ("HOOKS",) | io.Hooks.Input("id") | | ("LORA_MODEL",) | io.LoraModel.Input("id") | | ("MESH",) | io.Mesh.Input("id") | | ("VOXEL",) | io.Voxel.Input("id") | | ("FILE_3D",) | io.File3DAny.Input("id") | | ("FILE_3D_GLB",) | io.File3DGLB.Input("id") | | ("SVG",) | io.SVG.Input("id") | | ("COLOR",) | io.Color.Input("id") | | ("BOUNDING_BOX",) | io.BoundingBox.Input("id") | | ("CURVE",) | io.Curve.Input("id") | | ("LATENT_UPSCALE_MODEL",) | io.LatentUpscaleModel.Input("id") | | ("MODEL_PATCH",) | io.ModelPatch.Input("id") | | ("HOOK_KEYFRAMES",) | io.HookKeyframes.Input("id") | | ("AUDIO_ENCODER",) | io.AudioEncoder.Input("id") | | ("AUDIO_ENCODER_OUTPUT",) | io.AudioEncoderOutput.Input("id") | | ("TRACKS",) | io.Tracks.Input("id") | | ("LOSS_MAP",) | io.LossMap.Input("id") | | ("TIMESTEPS_RANGE",) | io.TimestepsRange.Input("id") | | ("LATENT_OPERATION",) | io.LatentOperation.Input("id") | | ("WEBCAM",) | io.Webcam.Input("id") | | ("PHOTOMAKER",) | io.Photomaker.Input("id") | | ("WAN_CAMERA_EMBEDDING",) | io.WanCameraEmbedding.Input("id") | | ("LOAD_3D",) | io.Load3D.Input("id") | | ("LOAD_3D_ANIMATION",) | io.Load3DAnimation.Input("id") | | ("LOAD3D_CAMERA",) | io.Load3DCamera.Input("id") | | ("FILE_3D_GLTF",) | io.File3DGLTF.Input("id") | | ("FILE_3D_FBX",) | io.File3DFBX.Input("id") | | ("FILE_3D_OBJ",) | io.File3DOBJ.Input("id") | | ("FILE_3D_STL",) | io.File3DSTL.Input("id") | | ("FILE_3D_USDZ",) | io.File3DUSDZ.Input("id") | | ("POINT",) | io.Point.Input("id") | | ("FACE_ANALYSIS",) | io.FaceAnalysis.Input("id") | | ("BBOX",) | io.BBOX.Input("id") | | ("SEGS",) | io.SEGS.Input("id") | | ("IMAGECOMPARE",) | io.ImageCompare.Input("id") | | ("*",) | io.AnyType.Input("id") or io.MultiType.Input("id", types=[...]) |

Method Migration

Execute Method

# V1: instance method with custom name
class V1Node:
    FUNCTION = "process"
    def process(self, image, value):
        return (result,)

# V3: classmethod named "execute", returns NodeOutput
class V3Node(io.ComfyNode):
    @classmethod
    def execute(cls, image, value):
        return io.NodeOutput(result)

IS_CHANGED → fingerprint_inputs

# V1
@classmethod
def IS_CHANGED(s, **kwargs):
    return float("NaN")  # always re-execute

# V3
@classmethod
def fingerprint_inputs(cls, **kwargs):
    import time
    return time.time()  # always re-execute

VALIDATE_INPUTS → validate_inputs

# V1
@classmethod
def VALIDATE_INPUTS(s, input_types=None, **kwargs):
    return True

# V3
@classmethod
def validate_inputs(cls, input_types=None, **kwargs):
    return True

check_lazy_status

# V1: instance method
def check_lazy_status(self, **kwargs):
    return ["input_name"]

# V3: classmethod
@classmethod
def check_lazy_status(cls, **kwargs):
    return ["input_name"]

Hidden Inputs

# V1: received as kwargs
def execute(self, image, unique_id=None, prompt=None):
    node_id = unique_id

# V3: accessed via cls.hidden
@classmethod
def execute(cls, image):
    node_id = cls.hidden.unique_id
    prompt = cls.hidden.prompt

Registration Migration

# V1
NODE_CLASS_MAPPINGS = {
    "Node1": Node1Class,
    "Node2": Node2Class,
}
NODE_DISPLAY_NAME_MAPPINGS = {
    "Node1": "Node One",
    "Node2": "Node Two",
}
WEB_DIRECTORY = "./js"

# V3
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io

class MyExtension(ComfyExtension):
    @override
    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return [Node1Class, Node2Class]

    @override
    async def on_load(self):
        # Optional: initialization logic
        pass

async def comfy_entrypoint() -> MyExtension:
    return MyExtension()

# WEB_DIRECTORY still works the same way for JS extensions
WEB_DIRECTORY = "./js"

Output Node Migration

# V1
class V1SaveNode:
    RETURN_TYPES = ()
    OUTPUT_NODE = True
    FUNCTION = "save"

    def save(self, images, prefix):
        # ... save logic ...
        return {"ui": {"images": results}}

# V3
from comfy_api.latest import io, ui

class V3SaveNode(io.ComfyNode):
    @classmethod
    def define_schema(cls):
        return io.Schema(
            node_id="V3SaveNode",
            display_name="Save",
            category="image",
            is_output_node=True,
            inputs=[
                io.Image.Input("images"),
                io.String.Input("prefix", default="output"),
            ],
            outputs=[],
            hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo],
        )

    @classmethod
    def execute(cls, images, prefix):
        saved = ui.ImageSaveHelper.get_save_images_ui(images, prefix, cls=cls)
        return io.NodeOutput(ui=saved)

Key Gotchas

No instance state: V3 execute is a classmethod. Don't store state on self. Use external storage if needed.
Fixed method name: Always execute, never custom names.
Hidden access changed: Use cls.hidden.prompt not function parameters.
Return type changed: io.NodeOutput(val) not (val,).
Optional inputs: Use =None default in execute params, not separate "optional" dict.
Async support: V3 execute can be async def execute(cls, ...).

comfyui-node-migration