# Flux Dev — Atlas Cloud API

> Flux-dev text to image model, 12 billion parameter rectified flow transformer.

This is the machine-readable API reference for **Flux Dev** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `black-forest-labs/flux-dev`
- **Built by**: Black Forest Labs
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/black-forest-labs/flux-dev
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.012 per image
- Pay-as-you-go. No minimum spend, no subscription required.

> **These are the authoritative Atlas Cloud rates for this model.** Any price that
> appears in the vendor description further down refers to a different platform or
> a different model variant and does not apply here.

## Use this model from an AI agent

Atlas Cloud ships three first-party integration surfaces. All three authenticate
with the same API key via the `ATLASCLOUD_API_KEY` environment variable.

### MCP server

The official MCP server (`atlascloud-mcp`) exposes this model to any
MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose,
Claude Desktop. One-line install:

```bash
# Claude Code
claude mcp add atlascloud -- npx -y atlascloud-mcp

# OpenAI Codex CLI
codex mcp add atlascloud -- npx -y atlascloud-mcp

# Gemini CLI
gemini mcp add atlascloud -- npx -y atlascloud-mcp

export ATLASCLOUD_API_KEY="your-api-key"
```

Then ask in plain English; the agent calls `atlas_generate_image` with `model: "black-forest-labs/flux-dev"`.
The server fetches each model's schema and validates parameters before submitting,
so invalid requests fail fast without spending credits.

MCP docs: https://www.atlascloud.ai/docs/mcp-server

### Agent Skills

`atlas-cloud-skills` is a portable skill package (API reference, code templates in
Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and
12+ other agents:

```bash
npx skills add AtlasCloudAI/atlas-cloud-skills
export ATLASCLOUD_API_KEY="your-api-key"
```

Skills docs: https://www.atlascloud.ai/docs/skills

### CLI

The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs
are polled and downloaded automatically (use `--no-download` when a script only
needs the output URLs):

```bash
# Install (Homebrew, npm, or shell installer)
brew install AtlasCloudAI/tap/atlascloud
# npm install -g atlascloud-cli
# curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh

atlas auth login
atlas generate image black-forest-labs/flux-dev -p "Your prompt here"
```

CLI docs: https://www.atlascloud.ai/docs/cli

## HTTP API reference

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `black-forest-labs/flux-dev`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"black-forest-labs/flux-dev"`

- **`prompt`** (`string`, _required_):
  The prompt to generate an image from.
  - Default: `"A stylish model, fashion show, showcase a designer outfit, orange colour suit, conspicuous jewelry, fashion show background, vibrant color, dramatic makeup"`

- **`image`** (`string`, _optional_):
  The image to generate an image from.
  - Default: `""`

- **`mask_image`** (`string`, _optional_):
  The mask image tells the model where to generate new pixels (white) and where to preserve the original image (black). It acts as a stencil or guide for targeted image editing.

- **`strength`** (`number`, _optional_):
  Strength indicates extent to transform the reference image
  - Default: `0.8`
  - Min: 0
  - Max: 1

- **`size`** (`string`, _optional_):
  The size of the generated image.
  - Default: `"1024*1024"`

- **`num_inference_steps`** (`integer`, _optional_):
  The number of inference steps to perform.
  - Default: `28`
  - Min: 1
  - Max: 50

- **`seed`** (`integer`, _optional_):
  
            The same seed and the same prompt given to the same version of the model
            will output the same image every time.
        
  - Default: `-1`

- **`guidance_scale`** (`number`, _optional_):
  Flux embedded guidance strength. Higher values make the image follow the prompt more closely. This is not True CFG and does not require a negative prompt. Default 3.5.
  - Default: `3.5`
  - Min: 1
  - Max: 20

- **`num_images`** (`integer`, _optional_):
  The number of images to generate.
  - Default: `1`
  - Min: 1
  - Max: 4

- **`enable_base64_output`** (`boolean`, _optional_):
  If enabled, the output will be encoded into a BASE64 string instead of a URL.
  - Default: `false`

- **`enable_safety_checker`** (`boolean`, _optional_):
  If set to true, the safety checker will be enabled.
  - Default: `true`



**Required Parameters Example**:

```json
{
  "model": "black-forest-labs/flux-dev",
  "prompt": "A stylish model, fashion show, showcase a designer outfit, orange colour suit, conspicuous jewelry, fashion show background, vibrant color, dramatic makeup"
}
```


**Full Example**:

```json
{
  "model": "black-forest-labs/flux-dev",
  "prompt": "A stylish model, fashion show, showcase a designer outfit, orange colour suit, conspicuous jewelry, fashion show background, vibrant color, dramatic makeup",
  "image": "",
  "mask_image": "",
  "strength": 0.8,
  "size": "1024*1024",
  "num_inference_steps": 28,
  "seed": -1,
  "guidance_scale": 3.5,
  "num_images": 1,
  "enable_base64_output": false,
  "enable_safety_checker": true
}
```


### Output Schema

The API returns the following output format:


- **`id`** (`string`, _optional_):
  Unique prediction ID

- **`logs`** (`string`, _optional_):
  Execution logs

- **`urls`** (`string`, _optional_):

- **`input`** (`string`, _optional_):

- **`model`** (`string`, _optional_):
  Model name

- **`output`** (`array[string]`, _optional_):
  Generated output URLs

- **`status`** (`string`, _optional_):
  Prediction status
  - Options: "queued", "processing", "succeeded", "failed"

- **`created_at`** (`string`, _optional_):
  Creation timestamp

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  NSFW content detection results



**Example Response**:

```json
{
  "id": "",
  "logs": "",
  "urls": null,
  "input": null,
  "model": "",
  "output": [
    ""
  ],
  "status": "queued",
  "created_at": "",
  "has_nsfw_contents": []
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "black-forest-labs/flux-dev",
  "prompt": "A stylish model, fashion show, showcase a designer outfit, orange colour suit, conspicuous jewelry, fashion show background, vibrant color, dramatic makeup",
  "image": "",
  "mask_image": "",
  "strength": 0.8,
  "size": "1024*1024",
  "num_inference_steps": 28,
  "seed": -1,
  "guidance_scale": 3.5,
  "num_images": 1,
  "enable_base64_output": false,
  "enable_safety_checker": true
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/black-forest-labs/flux-dev)

## About this model

_Vendor-supplied description. Any pricing or endpoint mentioned below refers to_
_other platforms — use the Atlas Cloud values above._

### Flux-Dev

flux-dev is a 12 billion parameter rectified flow transformer capable of generating images from textual descriptions.

#### Key Features

*   **High-Quality Image Generation**: Produces detailed and visually appealing images from textual prompts.
*   **Efficient Training with Guidance Distillation**: Utilizes guidance distillation techniques to enhance training efficiency and model responsiveness.
*   **Open Weights**: Provides open access to model weights, facilitating scientific research and creative development.
*   **Versatile Usage**: Suitable for personal, scientific, and commercial applications, offering flexibility across various use cases.

#### Limitations

*   **Creative Focus**: Designed primarily for creative image synthesis; not intended for generating factually accurate content.
*   **Inherent Biases**: Outputs may reflect biases present in the training data.
*   **Input Sensitivity**: The quality and consistency of generated images depend significantly on the quality of the input text; subtle variations may lead to output variability.
*   **Prompt Dependency**: The model's performance is closely tied to the clarity and structure of the prompts; careful crafting may be necessary for optimal results.

#### Out-of-Scope Use

The model and its derivatives may not be used in any way that violates applicable national, federal, state, local, or international law or regulation, including but not limited to:

_(Description truncated. Full text on the model page.)_

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/black-forest-labs/flux-dev · Docs: https://www.atlascloud.ai/docs