black-forest-labs

flux-1.1-pro

Warm

Faster, better FLUX Pro. Text-to-image model with excellent image quality, prompt adherence, and output diversity.

Official

48.4M runs

$0.04 per output image

Commercial use

Run with an API

Pricing

License

Playground API Examples README

Input

prompt

*string

Shift + Return to add a new line

black forest gateau cake spelling out the words "FLUX 1 . 1 Pro", tasty, food photographyblack forest gateau cake spelling out the words "FLUX 1 . 1 Pro", tasty, food photography

Text prompt for image generation

image_prompt

file

Image to use with Flux Redux. This is used together with the text prompt to guide the generation towards the composition of the image_prompt. Must be jpeg, png, gif, or webp.

aspect_ratio

string

Aspect ratio for the generated image

Default: "1:1"

width

integer

(minimum: 256, maximum: 1440)

Width of the generated image in text-to-image mode. Only used when aspect_ratio=custom. Must be a multiple of 32 (if it's not, it will be rounded to nearest multiple of 32). Note: Ignored in img2img and inpainting modes.

height

integer

(minimum: 256, maximum: 1440)

Height of the generated image in text-to-image mode. Only used when aspect_ratio=custom. Must be a multiple of 32 (if it's not, it will be rounded to nearest multiple of 32). Note: Ignored in img2img and inpainting modes.

safety_tolerance

integer

(minimum: 1, maximum: 6)

Safety tolerance, 1 is most strict and 6 is most permissive

Default: 2

seed

integer

Random seed. Set for reproducible generation

prompt_upsampling

boolean

Automatically modify the prompt for more creative generation

Default: false

output_format

string

Format of the output images.

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

Default: 80

Run this model in Node.js with one line of code:

npx create-replicate --model=black-forest-labs/flux-1.1-pro

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run black-forest-labs/flux-1.1-pro using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  prompt: "black forest gateau cake spelling out the words \"FLUX 1 . 1 Pro\", tasty, food photography",
  aspect_ratio: "1:1",
  output_format: "webp",
  output_quality: 80,
  safety_tolerance: 2,
  prompt_upsampling: true
};

const output = await replicate.run("black-forest-labs/flux-1.1-pro", { input });

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run black-forest-labs/flux-1.1-pro using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "black-forest-labs/flux-1.1-pro",
    input={
        "prompt": "black forest gateau cake spelling out the words \"FLUX 1 . 1 Pro\", tasty, food photography",
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "safety_tolerance": 2,
        "prompt_upsampling": True
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run black-forest-labs/flux-1.1-pro using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "input": {
      "prompt": "black forest gateau cake spelling out the words \\"FLUX 1 . 1 Pro\\", tasty, food photography",
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "safety_tolerance": 2,
      "prompt_upsampling": true
    }
  }' \
  https://api.replicate.com/v1/models/black-forest-labs/flux-1.1-pro/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Generated in

3.8 seconds

Tweak it Iterate in playground Report View full prediction

Examples

View more examples

Pricing

Model pricing for black-forest-labs/flux-1.1-pro. Looking for volume pricing? Get in touch.

$0.04

per output image

or 25 images for $1

Official models are always on, maintained, and have predictable pricing. Learn more.

Check out our docs for more information about how pricing works on Replicate.

Readme

FLUX1.1 [pro] provides six times faster generation than its predecessor FLUX.1 [pro] while also improving image quality, prompt adherence, and diversity.

Superior Speed and Efficiency: Faster generation times and reduced latency, enabling more efficient workflows. FLUX1.1 [pro] provides an ideal tradeoff between image quality and inference speed.
Improved Performance: FLUX1.1 [pro] has been introduced and tested under the codename “blueberry” into the Artificial Analysis image arena, a popular benchmark for text-to-image models. It surpasses all other models on the leaderboard, achieving the highest overall Elo score.

Read the announcement from Black Forest Labs here.

All public FLUX.1 models are based on a hybrid architecture of multimodal and parallel diffusion transformer blocks and scaled to 12B parameters. We improve over previous state-of-the-art diffusion models by building on flow matching, a general and conceptually simple method for training generative models, which includes diffusion as a special case. In addition, we increase model performance and improve hardware efficiency by incorporating rotary positional embeddings and parallel attention layers.

License

By using FLUX.1 [pro] through Replicate you agree to the Black Forest Labs API agreement and the Black Forest Labs Terms of Service.