Latent Consistency Models (v1.5/XL)

Commercial use

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/serverless-client

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.


Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import * as fal from "@fal-ai/serverless-client";

const result = await fal.subscribe("fal-ai/fast-lcm-diffusion", {
  input: {
    prompt: "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k."
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") { => log.message).forEach(console.log);

Real-time via WebSockets#

This model has a real-time mode via websockets, this is supported via the fal.realtime client.

import * as fal from "@fal-ai/serverless-client";

const connection = fal.realtime.connect("fal-ai/fast-lcm-diffusion", {
  onResult: (result) => {
  onError: (error) => {

  prompt: "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k."

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import * as fal from "@fal-ai/serverless-client";

  credentials: "YOUR_FAL_KEY"

3. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import * as fal from "@fal-ai/serverless-client";

// Upload a file (you can get a file reference from an input element or a drag-and-drop event)
const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await;

// Use the URL in your request
const result = await fal.subscribe("fal-ai/fast-lcm-diffusion", { image_url: url });

Read more about file handling in our file upload guide.

4. Schema#



The name of the model to use. Default value: "stabilityai/stable-diffusion-xl-base-1.0"

Possible values: "stabilityai/stable-diffusion-xl-base-1.0", "runwayml/stable-diffusion-v1-5"


The prompt to use for generating the image. Be as descriptive as possible for best results.


The negative prompt to use. Use it to address details that you don't want in the image. This could be colors, objects, scenery and even the small details (e.g. moustache, blurry, low resolution). Default value: ""

image_sizeImageSize | Enum

The size of the generated image. Default value: square_hd

Possible values: "square_hd", "square", "portrait_4_3", "portrait_16_9", "landscape_4_3", "landscape_16_9"


The number of inference steps to perform. Default value: 6


The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.


The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. Default value: 1.5


If set to true, the function will wait for the image to be generated and uploaded before returning the response. This will increase the latency of the function but it allows you to get the image directly in the response without going through the CDN. Default value: true


The number of images to generate. Default value: 1


If set to true, the safety checker will be enabled. Default value: true


The version of the safety checker to use. v1 is the default CompVis safety checker. v2 uses a custom ViT model. Default value: "v1"

Possible values: "v1", "v2"


If set to true, the prompt will be expanded with additional prompts.


The format of the generated image. Default value: "jpeg"

Possible values: "jpeg", "png"


The rescale factor for the CFG.


An id bound to a request, can be used with response to identify the request itself. Default value: ""

  "model_name": "stabilityai/stable-diffusion-xl-base-1.0",
  "prompt": "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k.",
  "negative_prompt": "cartoon, illustration, animation. face. male, female",
  "image_size": "square_hd",
  "num_inference_steps": 6,
  "guidance_scale": 1.5,
  "sync_mode": true,
  "num_images": 1,
  "enable_safety_checker": true,
  "safety_checker_version": "v1",
  "format": "jpeg"



The generated image files info.


Seed of the generated Image. It will be the same value of the one passed in the input or the randomly generated that was used in case none was passed.


Whether the generated images contain NSFW concepts.


The prompt used for generating the image.

  "images": [
      "url": "",
      "content_type": "image/jpeg"
  "prompt": ""