stability-ai/stable-video
Stable Video by Stability AI - animate still images into dynamic videos with AI. Transform photos into cinematic clips with natural motion, camera movement, and optional audio generation.
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/stable-videoInput Schema
5 parameters · 1 required · 4 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
image | string | Required | The URL of the image to use as a starting point for the generation. · Min length: 1 |
fps | integer | Optional | The frames per second of the generated video. · Min: 10 · Max: 100 · Default: 25 |
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. |
cond_aug | number | Optional | The conditoning augmentation determines the amount of noise that will be added to the conditioning frame. The higher the number, the more noise there will be, and the less the video will look like the initial image. Increase it for more motion. · Min: 0 · Max: 10 · Default: 0.02 |
motion_bucket_id | integer | Optional | The motion bucket id determines the motion of the generated video. The higher the number, the more motion there will be. · Min: 1 · Max: 255 · Default: 127 |
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/stable-video",
"fps": 25,
"image": "https://static.sandbase.ai/examples/stability/stable-video/input_image_0.png",
"cond_aug": 0.02,
"motion_bucket_id": 127,
"prompt": "a beautiful sunset over mountains"
}'
# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
-H "Authorization: Bearer YOUR_API_KEY"API README
High Quality Stable Video Diffusion
High Quality Stable Video Diffusion occupies a clearly bounded position in a video production pipeline under the route stability-ai/stable-video. 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 High Quality Stable Video Diffusion should begin with source-readiness checks, ownership of the submitted material, an agreed budget, and a written definition of the final stable video 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/stable-video.
Highlights
- Distinct output behavior. For High Quality Stable Video Diffusion, for High Quality Stable Video Diffusion, transform photos into cinematic clips with natural motion In High Quality Stable Video Diffusion, this capability is applied through the exact stability-ai/stable-video workflow with fps as a relevant request control; the fps control exposes the corresponding choice in this route; the fps control exposes the corresponding choice in this route.
- Creative control. For High Quality Stable Video Diffusion, for High Quality Stable Video Diffusion, optional audio generation In High Quality Stable Video Diffusion, this capability is applied through the exact stability-ai/stable-video 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.
- Workflow fit. For High Quality Stable Video Diffusion, for High Quality Stable Video Diffusion, image to video In High Quality Stable Video Diffusion, this capability is applied through the exact stability-ai/stable-video workflow with image as a relevant request control; the image control exposes the corresponding choice in this route; the image control exposes the corresponding choice in this route.
- Production detail. For High Quality Stable Video Diffusion, for High Quality Stable Video Diffusion, the conditoning augmentation determines the amount of noise that will be added to the conditioning frame. The higher the number, the more noise there will be, and the less the video will look like the initial image. Increase it for more motion In High Quality Stable Video Diffusion, this capability is applied through the exact stability-ai/stable-video workflow with cond aug as a relevant request control; the cond aug control exposes the corresponding choice in this route; the cond aug control exposes the corresponding choice in this route.
Pricing
| Configuration | Price |
|---|---|
| Per request | $0.075 |
When to Use
| Scenario | Why this model fits |
|---|---|
| Choose High Quality Stable Video Diffusion | Use it when the required deliverable is specifically the video result documented for stability-ai/stable-video. |
| Match the source material | Select this route when your inputs naturally map to fps, seed, image, cond_aug. |
| Use its distinguishing capability | For High Quality Stable Video Diffusion, transform photos into cinematic clips with natural motion In High Quality Stable Video Diffusion, this capability is applied through the exact stability-ai/stable-video workflow with fps as a relevant request control; the fps control exposes the corresponding choice in this route |
| Plan repeatable production | For High Quality Stable Video Diffusion, optional audio generation In High Quality Stable Video Diffusion, this capability is applied through the exact stability-ai/stable-video workflow with seed as a relevant request control; the seed 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 High Quality Stable Video Diffusion jobs. |
Prompt Guide
Build the request around the exact stability-ai/stable-video 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.
{
"image": "https://static.sandbase.ai/examples/stability/stable-video/input_image_0.png",
"fps": 25,
"seed": 0,
"cond_aug": 0.02
}
Technical Specs
| Specification | Value |
|---|---|
| Model ID | stability-ai/stable-video |
| Execution mode | async |
| Required inputs | image |
| Request fields | fps (integer, optional, min 10, max 100); seed (integer, optional); image (string, required); cond_aug (number, optional, min 0, max 10); motion_bucket_id (integer, optional, min 1, max 255) |
| Output | url (string); content_type (string) |