SkyReels V1
Playground
Try it on WavespeedAI!SkyReels V1 is an open-source, human-centric video foundation model fine-tuned from HunyuanVideo on ~10M high-quality film and TV clips to deliver realistic human motion and scene synthesis. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
SkyReels V1 — wavespeed-ai/SkyReels-V1
SkyReels V1 is an image-to-video model that animates a single reference image into a short, cinematic clip guided by a text prompt. Upload an image to anchor the subject and composition, then describe the motion, camera language, atmosphere, and visual style you want. The model is well-suited for nature shots, cinematic macro moments, and smooth “living photo” style animations, with seed control for reproducible variations.
Key capabilities
- Image-to-video generation anchored to a reference image
- Prompt-driven motion, atmosphere, and camera intent
- Works well for cinematic “living photo” animation and natural motion
- Seed control for reproducible outputs
Use cases
- Animate nature photography (birds, insects, plants, weather, light rays)
- Cinematic macro shots (wings fluttering, pollen drifting, dew shimmering)
- Turning a still image into a short b-roll clip for edits and trailers
- Rapid iteration: generate multiple takes by changing prompt or seed
- Stylized scene animation with consistent composition
Pricing
| Output | Price per run |
|---|---|
| Image-to-Video (per generation) | $0.20 |
Inputs
- prompt (required): what happens in the video (action + scene + camera)
- image (required): reference image (subject/composition anchor)
Parameters
- prompt: describe subject, motion, environment, camera, and style
- image: input image (upload or URL)
- seed: random seed (-1 for random; fixed value for reproducible results)
Prompting guide (I2V)
For stronger results, write prompts like a director’s brief:
- Subject: who/what is on screen
- Action: what moves over time (flutter, drift, sway, shimmer)
- Scene: where it happens + time/lighting
- Camera: macro close-up, slow push-in, gentle pan (optional)
- Constraints: keep composition consistent with the reference image
Example prompts
- Amazon rainforest at dawn, sun rays piercing the canopy, a hummingbird hovering by an orchid, wings vibrating rapidly, macro lens, shallow depth of field, drifting pollen and dust motes, slow cinematic push-in, natural motion.
- A close-up of a flower with dew drops sparkling, gentle breeze moving petals, soft morning light, subtle camera pan, realistic motion, cinematic b-roll.
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/wavespeed-ai/SkyReels-V1" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| image | string | Yes | - | URL of the image input. | |
| seed | integer | No | - | -1 ~ 2147483647 | The random seed to use for the generation. |
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 (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.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 |