> ## Documentation Index
> Fetch the complete documentation index at: https://docs.runcomfy.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

<Warning>
  **API v1 is being deprecated — please migrate to v2.** All new integrations should use the `/prod/v2/...` endpoints. v1 remains available for now but will not receive new features and will be retired in a future release.
</Warning>

**Serverless API (ComfyUI)** lets you turn a **cloud-saved ComfyUI workflow** into a **callable, scalable endpoint** (a *Deployment*).

You deploy a workflow once, then your application calls that deployment by `deployment_id` using an async queue API (submit → get `request_id` → poll status/result, or receive updates via webhooks).

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## What you get

With Serverless API (ComfyUI) you can:

* **Deploy a workflow as an API**, no infra to manage (RunComfy handles containerization + GPU orchestration)
* **Choose hardware per deployment** (GPU/VRAM tier) and change it later if requirements evolve
* **Autoscale** with explicit knobs (min/max instances, queue threshold, keep-warm duration)
* **Version workflows** safely (deployments are pinned to a workflow version; upgrades are explicit and reversible)
* **Integrate in production** with **webhooks** and the **instance proxy** for advanced operations

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## Key objects

* **Workflow (cloud-saved)**: a ComfyUI workflow packaged together with its runtime (nodes, models, dependencies).
* **Workflow version**: each Cloud Save creates an immutable version (like a container image snapshot).
* **Deployment**: the serverless endpoint you call (identified by `deployment_id`), pinned to a workflow version.
* **Request**: a single async inference job against a deployment (identified by `request_id`).
* **Instance**: a running container for a deployment that actually executes requests; instances scale up/down based on your autoscaling settings.

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## Typical workflow

1. Build or customize a workflow in RunComfy’s ComfyUI Cloud.
2. **Cloud Save** the workflow (creates a version).
3. Create a **Deployment** (choose hardware + autoscaling).
4. Submit inference: `POST /prod/v2/deployments/{deployment_id}/inference`
5. Poll status/result (or use webhooks).

Next step: **[Quickstart](/serverless/quickstart)**

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## How this relates to the other RunComfy APIs

* **[Model API](/model-apis/quickstart)**: on-demand inference for hosted models/pipelines, **no deployment**, **per-request billing**, call by `model_id`.
* **[Serverless API (LoRA)](/serverless-lora/introduction)**: built on the same serverless deployment system, but what you deploy is a **Trainer LoRA** (instead of a workflow).

***

## Alternative option: Server API (ComfyUI)

If you need full control of a dedicated ComfyUI backend instance (for example, to integrate ComfyUI directly into tools like Krita, Photoshop, Blender, iClone, etc.), RunComfy also provides a **Server API** paired with the **ComfyUI Backend API**.

See the Server API documentation here: [RunComfy ComfyUI Backend API](https://comfyui-guides.runcomfy.com/api-reference)