meituan/longcat-image/edit
Longcat Image Edit by sandbase-ai - AI-powered image editing, style transfer, and transformation. Edit photos with natural language instructions, remove backgrounds, change styles, and enhance images effortlessly.
PNG, JPEG, WebP, or GIF · 20 MiB maximum
Example output — click Run to generate your own
Send your first request
OpenAI-compatible endpoint with unified authentication and usage tracking.
https://api.sandbase.ai/v1/runmeituan/longcat-image/editInput Schema
6 parameters · 2 required · 4 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
image | string | Required | The URL of the image to edit. |
prompt | string | Required | The prompt to edit the image with. |
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. |
output_format | string | Optional | The format of the generated image. · Options: jpeg, png · Default: "png" jpegpng |
guidance_scale | number | Optional | The guidance scale to use for the image generation. · Min: 1 · Max: 20 · Default: 4.5 |
num_inference_steps | integer | Optional | The number of inference steps to perform. · Min: 1 · Max: 50 · Default: 28 |
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
Async Workflow
This model uses asynchronous execution. Submit a request and poll for the result.
- Submit — POST to /v1/run, receive an
id - Poll — GET /v1/run/{id} until status is
completed,failed, ortimeout - Retrieve — Read
outputsfrom the completed response
Code Examples
Ready-to-run snippets
# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "meituan/longcat-image/edit",
"image": "https://static.sandbase.ai/examples/alibaba/qwen-image/edit/input_image_0.png",
"prompt": "Add the text \"Fal is fast\" in elegant cursive font with lightning streaks at the top of the image.",
"output_format": "png",
"guidance_scale": 4.5,
"num_inference_steps": 28
}'
# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
-H "Authorization: Bearer YOUR_API_KEY"API README
Longcat Image
Longcat Image is a LongCat route built for prompt-guided image editing. It turns one or more source images and a precise change request into a revised image that follows the edit while retaining intended structure, giving creators a focused endpoint instead of forcing one generic workflow across materially different production tasks. The route belongs to a family known for efficient generation, stable visual continuity, and practical media workflows, so it is best evaluated as a creative system for intentional shots and assets rather than as a one-click novelty generator.
Use this endpoint when the input contract and deliverable match that job exactly. Its documented controls include seed ( The same seed and the same prompt given to the same version of the model will output the same image every time. ); output_format choices (jpeg, png); guidance_scale (The guidance scale to use for the image generation); num_inference_steps (The number of inference steps to perform). Together, these controls help teams plan predictable iterations, compare outputs under stable settings, and connect generation to high-volume creative iteration and avatar or video production without hiding the operational choices that shape the result.
Highlights
- Purpose-built Prompt-guided image editing. The route accepts one or more source images and a precise change request and produces a revised image that follows the edit while retaining intended structure; its interface is scoped to that transformation, keeping source assets and creative intent explicit.
- Creative direction. Prompts can describe subject behavior, composition, camera intent, lighting, material, atmosphere, and temporal progression so the result is driven by a shot plan rather than isolated keywords.
- Route-specific control. The request exposes seed ( The same seed and the same prompt given to the same version of the model will output the same image every time. ); output_format choices (jpeg, png); guidance_scale (The guidance scale to use for the image generation); num_inference_steps (The number of inference steps to perform), allowing the same concept to be tested systematically while preserving a repeatable production setup.
- Pipeline-ready output. The generated media asset is returned through the documented asynchronous output contract, which suits review queues, batch iteration, and downstream automation. Editors can review pacing, continuity, lens language, choreography, transitions, temporal artifacts, soundtrack alignment, color response, delivery framing, and cut compatibility before approval.
Pricing
| Configuration | Price |
|---|---|
| Standard request | $0.150000 |
When to Use
| Scenario | Why this model fits |
|---|---|
| Create the exact route output | Choose it when you need prompt-guided image editing and already have one or more source images and a precise change request. |
| Develop controlled variations | Keep the main brief fixed while changing one documented setting at a time to compare motion, framing, quality, or asset behavior. |
| Build repeatable batches | Use a consistent request shape for catalog, campaign, storyboard, game-asset, or social-content production. |
| Preserve source intent | Prefer this route when the supplied reference material must remain the foundation of a revised image that follows the edit while retaining intended structure. |
| Connect a media pipeline | Use asynchronous results in an automated review, approval, post-production, or asset-management workflow. |
Prompt Guide
Start with the desired result, then describe the source relationship, subject action, composition or camera behavior, lighting, style, and timing. For prompt-guided image editing, state what must remain stable as clearly as what should change. Use only fields exposed by the schema; the example below is structurally valid for this route.
{
"prompt": "Add the text \"Fal is fast\" in elegant cursive font with lightning streaks at the top of the image.",
"image": "https://static.sandbase.ai/examples/alibaba/qwen-image/edit/input_image_0.png",
"seed": 1,
"output_format": "png",
"guidance_scale": 4.5
}
Technical Specs
| Specification | Value |
|---|---|
| Model ID | meituan/longcat-image/edit |
| Workflow | Prompt-guided image editing |
| Required inputs | prompt, image |
seed | integer |
image | string |
prompt | string |
output_format | string; options: jpeg, png |
guidance_scale | number; minimum: 1; maximum: 20 |
num_inference_steps | integer; minimum: 1; maximum: 50 |