# Grok Imagine Image Quality Edit — Atlas Cloud API

> xAI Grok Imagine edits one or more reference images with natural-language instructions at 1K or 2K resolution. Supports single image and multi-image (<IMAGE_0>, <IMAGE_1>) reference editing.

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

- **Model ID**: `xai/grok-imagine-image-quality/edit`
- **Built by**: xAI
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/xai/grok-imagine-image-quality/edit
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.05 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: "xai/grok-imagine-image-quality/edit"`.
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 xai/grok-imagine-image-quality/edit -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**: `xai/grok-imagine-image-quality/edit`


## 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: `"xai/grok-imagine-image-quality/edit"`

- **`prompt`** (`string`, _required_):
  Editing instruction. For multi-image references, cite each input as <IMAGE_0>, <IMAGE_1>, ...
  - Default: `"Render this as a pencil sketch with detailed shading."`

- **`image_urls`** (`array[string]`, _required_):
  Source images. Each entry is either a public URL or a base64-encoded data URI (e.g. `data:image/png;base64,...`). At least one image is required; each input is billed at $0.01.
  - Min items: 1
  - Max items: 8

- **`num_images`** (`integer`, _optional_):
  Number of edited images to generate. Each output image is billed separately.
  - Default: `1`
  - Options: 1, 2, 3, 4

- **`aspect_ratio`** (`string`, _optional_):
  Aspect ratio of the edited image. With a single source image, the output respects the input's aspect ratio regardless of this value. `auto` lets the model pick.
  - Default: `"auto"`
  - Options: "auto", "1:1", "3:4", "4:3", "9:16", "16:9", "2:3", "3:2", "9:19.5", "19.5:9", "9:20", "20:9", "1:2", "2:1"

- **`resolution`** (`string`, _optional_):
  Output resolution. 1k = 1024x1024 ($0.05/image), 2k = 2048x2048 ($0.07/image).
  - Default: `"1k"`
  - Options: "1k", "2k"

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



**Required Parameters Example**:

```json
{
  "model": "xai/grok-imagine-image-quality/edit",
  "prompt": "Render this as a pencil sketch with detailed shading.",
  "image_urls": [
    ""
  ]
}
```


**Full Example**:

```json
{
  "model": "xai/grok-imagine-image-quality/edit",
  "prompt": "Render this as a pencil sketch with detailed shading.",
  "image_urls": [
    ""
  ],
  "num_images": 1,
  "aspect_ratio": "auto",
  "resolution": "1k",
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the edited images (empty when status is not completed).

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.



**Example Response**:

```json
{
  "id": "",
  "urls": {},
  "model": "",
  "status": "",
  "outputs": [
    ""
  ],
  "created_at": ""
}
```


## 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": "xai/grok-imagine-image-quality/edit",
  "prompt": "Render this as a pencil sketch with detailed shading.",
  "image_urls": [
    ""
  ],
  "num_images": 1,
  "aspect_ratio": "auto",
  "resolution": "1k",
  "enable_base64_output": false
}'

# 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/xai/grok-imagine-image-quality/edit)

## About this model

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

#### 1. Introduction

**Grok Imagine Image Quality** is xAI's flagship image generation and editing system, also known as "Quality Mode," designed to deliver photorealistic imagery, legible in-image typography, and tight prompt adherence across diverse visual styles. This README applies to the following API model identifiers:

- `xai/grok-imagine-image-quality/text-to-image`
- `xai/grok-imagine-image-quality/edit`

Developed by xAI and built on the Aurora foundation—an autoregressive Mixture-of-Experts (MoE) architecture that differentiates it from diffusion-based competitors—Grok Imagine Image Quality targets creators, developers, and enterprises who require high-fidelity static imagery alongside natural-language editing. The consumer version launched on April 3, 2026 via grok.com/imagine and the Grok iOS/Android apps, and the API became publicly available on May 6, 2026 through the [official announcement](https://x.ai/news/grok-imagine-quality-mode).

The system is exposed through two API variants that share the same underlying model but are optimized for distinct workflows. The `xai/grok-imagine-image-quality/text-to-image` endpoint produces images from text prompts with approximately 4-second latency, while `xai/grok-imagine-image-quality/edit` applies prompt-driven modifications to existing images—including multi-image reference composition—with approximately 13-second latency.

---

#### 2. Key Features & Innovations

- **Aurora MoE Architecture**: Unlike most image generators that rely on diffusion, Grok Imagine Image Quality is powered by Aurora, an autoregressive Mixture-of-Experts model. This approach yields strong facial consistency, accurate textures, and cinematic lighting behavior that reviewers have compared favorably with diffusion competitors on photorealistic sharpness.

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

---

Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/xai/grok-imagine-image-quality/edit · Docs: https://www.atlascloud.ai/docs