X Ai Grok Imagine Image Edit
Playground
Try it on WavespeedAI!X-AI Grok Imagine Image enables precise image editing with xAI’s Grok Imagine model. Transform and modify images using text prompts with AI-powered precision. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Grok Imagine Image Edit
Grok Imagine Image Edit is X-AI’s image editing model that transforms existing images based on text prompts. Upload your source image and describe the changes you want — the model intelligently edits while maintaining visual coherence.
Why Choose This?
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Text-driven editing Modify images using natural language instructions for intuitive control.
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Context-aware modifications Understands scene structure and object relationships for coherent edits.
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Style preservation Maintains the original image’s visual quality during edits.
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Prompt Enhancer Built-in tool to automatically improve your editing instructions.
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Cost-effective Affordable per-image pricing for high-volume editing workflows.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text instruction describing the desired edit |
| image | Yes | Source image to edit (URL or upload) |
How to Use
- Upload your image — provide the source image you want to edit.
- Write your prompt — describe the changes you want to make.
- Run — submit and download your edited image.
Pricing
| Output | Cost |
|---|---|
| Per image | $0.022 |
Best Use Cases
- Photo Retouching — Remove unwanted objects, fix imperfections, enhance details.
- Scene Modification — Change backgrounds, add or remove elements.
- Style Transfer — Apply different visual styles to existing images.
- Content Adaptation — Modify images for different contexts and platforms.
- Creative Exploration — Experiment with variations of existing visuals.
Pro Tips
- Use the Prompt Enhancer to refine your editing instructions.
- Be specific about what to change and what to preserve.
- Describe the desired outcome rather than the process (e.g., “the man wearing a red shirt” instead of “change the shirt color to red”).
- Use high-quality source images for better editing results.
- Combine with Grok Imagine Image T2I to generate base images, then edit.
Notes
- Both prompt and image are required fields.
- Ensure uploaded image URLs are publicly accessible.
- For best results, use clear and specific edit instructions.
Related Models
- Grok Imagine Image Text-to-Image — Generate images from text prompts.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/x-ai/grok-imagine-image/edit" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"num_images": 1,
"output_format": "png"
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The prompt to edit the image with. | |
| image | string | Yes | - | The source image to edit. | |
| num_images | integer | No | 1 | 1 ~ 10 | Number of images to generate (1-10). |
| output_format | string | No | png | png, jpeg | Output image format. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Array of URLs to the generated content (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
| data.model | string | Model ID used for the prediction |
| data.outputs | string | Array of URLs to the generated content. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |