# Comfyui Node Migration

> ComfyUI V1 to V3 node migration - converting legacy nodes to the V3 API. Use when migrating existing custom nodes from V1 to V3, understanding differences between API versions, or modernizing node code. Use when this capability is needed.

- Skill: `tomevault-io/comfyui-node-migration` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/comfyui-node-migration`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/comfyui-node-migration/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Integrations & APIs
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/comfyui-node-migration

---


# 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

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

## Side-by-Side Comparison

### V1 (Before)

```python
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)

```python
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

```python
# 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

```python
# 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

```python
# 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

```python
# 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

```python
# 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

```python
# 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

```python
# 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

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

## See Also

- `comfyui-node-basics` - V3 node fundamentals
- `comfyui-node-packaging` - Project structure
- `comfyui-node-lifecycle` - Execution lifecycle differences

---
> Source: [jtydhr88/comfyui-custom-node-skills](https://github.com/jtydhr88/comfyui-custom-node-skills) — distributed by [TomeVault](https://tomevault.io).
<!-- tomevault:4.0:skill_md:2026-06-24 -->