stability-ai/fast-sdxl-controlnet-canny
Fast Sdxl Controlnet Canny by Stability AI - generate stunning images from text prompts with state-of-the-art AI. Supports multiple aspect ratios, styles, and high-resolution output for creative and commercial use.
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/runstability-ai/fast-sdxl-controlnet-cannyInput Schema
7 parameters · 1 required · 6 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
prompt | string | Required | The prompt to use for generating the image. Be as descriptive as possible for best results. |
seed | integer | Optional | The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time. · Default: null |
loras | array | Optional | Default: [] |
aspect_ratio | string | Optional | The aspect ratio of the generated image. · Options: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16 21:916:93:24:35:41:14:53:42:39:16 |
guidance_scale | number | Optional | Min: 0 · Max: 20 · Default: 7.5 |
control_image_url | string | Optional | The URL of the control image. |
num_inference_steps | integer | Optional | Min: 1 · Max: 70 · Default: 35 |
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": "stability-ai/fast-sdxl-controlnet-canny",
"seed": null,
"loras": [],
"prompt": "Ice fortress, aurora skies, polar wildlife, twilight",
"guidance_scale": 7.5,
"control_image_url": "https://fal-cdn.batuhan-941.workers.dev/files/rabbit/MiN_j3St9B8esJleCZKMU.jpeg",
"num_inference_steps": 35
}'
# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
-H "Authorization: Bearer YOUR_API_KEY"API README
ControlNet SDXL
ControlNet SDXL occupies a clearly bounded position in a image production pipeline under the route stability-ai/fast-sdxl-controlnet-canny. It is best evaluated as a named workflow endpoint rather than as a generic substitute for neighboring versions: planners can assign the route to a specific brief, record the chosen revision, and keep approval history tied to one predictable integration surface from intake through delivery.
A practical rollout of ControlNet SDXL should begin with source-readiness checks, ownership of the submitted material, an agreed budget, and a written definition of the final fast sdxl controlnet canny deliverable. Before automation is enabled, the acceptance pass should verify that the returned asset opens correctly, fits the intended downstream toolchain, satisfies the project’s review criteria, and can be reproduced from the stored request and route identity stability-ai/fast-sdxl-controlnet-canny.
Highlights
- Distinct output behavior. For ControlNet SDXL, for ControlNet SDXL, keep the starting image and the Canny control image in their distinct request fields In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny workflow with seed as a relevant request control; the seed control exposes the corresponding choice in this route; the seed control exposes the corresponding choice in this route.
- Creative control. For ControlNet SDXL, for ControlNet SDXL, adjust how strongly the result resembles the initial image through the bounded strength value In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny workflow with loras as a relevant request control; the loras control exposes the corresponding choice in this route; the loras control exposes the corresponding choice in this route.
- Workflow fit. For ControlNet SDXL, for ControlNet SDXL, frame the result with one of the ten declared aspect ratios In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny workflow with prompt as a relevant request control; the prompt control exposes the corresponding choice in this route; the prompt control exposes the corresponding choice in this route.
- Production detail. For ControlNet SDXL, for ControlNet SDXL, tune inference steps from 1 through 70 In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny workflow with aspect ratio as a relevant request control; the aspect ratio control exposes the corresponding choice in this route; the aspect ratio control exposes the corresponding choice in this route.
Pricing
| Configuration | Price |
|---|---|
| Per request | $0.00125 |
When to Use
| Scenario | Why this model fits |
|---|---|
| Choose ControlNet SDXL | Use it when the required deliverable is specifically the image result documented for stability-ai/fast-sdxl-controlnet-canny. |
| Match the source material | Select this route when your inputs naturally map to seed, loras, prompt, aspect_ratio. |
| Use its distinguishing capability | For ControlNet SDXL, keep the starting image and the Canny control image in their distinct request fields In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny workflow with seed as a relevant request control; the seed control exposes the corresponding choice in this route |
| Plan repeatable production | For ControlNet SDXL, adjust how strongly the result resembles the initial image through the bounded strength value In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny workflow with loras as a relevant request control; the loras control exposes the corresponding choice in this route |
| Confirm cost and delivery | Use the pricing combinations below and the output contract above when budgeting or automating ControlNet SDXL jobs. |
Prompt Guide
Build the request around the exact stability-ai/fast-sdxl-controlnet-canny schema. Start with required fields, then add only the controls needed for the intended output; keep URLs reachable and enum values exactly as shown in Technical Specs.
{
"prompt": "Ice fortress, aurora skies, polar wildlife, twilight",
"seed": 0,
"loras": [],
"aspect_ratio": "21:9"
}
Technical Specs
| Specification | Value |
|---|---|
| Model ID | stability-ai/fast-sdxl-controlnet-canny |
| Execution mode | async |
| Required inputs | prompt |
| Request fields | seed (integer, optional); loras (array, optional); prompt (string, required); aspect_ratio (string, optional, options: 21:9 / 16:9 / 3:2 / 4:3 / 5:4 / 1:1 / 4:5 / 3:4 / 2:3 / 9:16); guidance_scale (number, optional, min 0, max 20); control_image_url (string, optional); num_inference_steps (integer, optional, min 1, max 70) |
| Output | url (string); content_type (string) |