Runwayml Gen4 Aleph
Playground
Try it on WavespeedAI!RunwayML Gen4 Aleph is a Video-to-Video model for editing, transforming, and generating video at $0.18 per second. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Runway Gen4 Aleph
Transform your videos with natural language instructions. Runway Gen4 Aleph is a powerful video-to-video model that understands text prompts to edit, modify, and reimagine your footage — from removing objects to changing environments and styles.
Why It Looks Great
- Natural language editing: Simply describe what you want changed — remove objects, alter backgrounds, modify styles.
- Context-aware transformations: Understands scene structure and maintains visual coherence throughout edits.
- Reference image guidance: Optionally provide a reference image to guide the visual style or target appearance.
- Flexible aspect ratios: Supports 16:9, 4:3, 1:1, 3:4, and 9:16 for any output format.
- Prompt Enhancer: Built-in tool to help refine and improve your editing instructions.
- Temporal consistency: Maintains smooth, stable results across all frames.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text instruction describing the edit (e.g., “Remove people from the video”). |
| video | Yes | Source video file (upload or public URL). |
| aspect_ratio | No | Output aspect ratio: 16:9, 4:3, 1:1, 3:4, or 9:16. Default: 16:9. |
| reference_image | No | Reference image to guide style or appearance (upload or URL). |
How to Use
- Write your prompt — describe the transformation you want (e.g., “Remove people from the video”, “Change the sky to sunset”, “Make it look like a watercolor painting”).
- Use Prompt Enhancer (optional) — click the button to refine your instructions for better results.
- Upload your video — drag and drop or paste a public URL.
- Choose aspect ratio — select the output format that fits your needs.
- Add reference image (optional) — provide visual guidance for the target style.
- Run — click the button to start processing.
- Download — preview and save your transformed video.
Pricing
Per-second billing based on input video duration.
| Metric | Cost |
|---|---|
| Per second | $0.18 |
Examples
| Video Length | Calculation | Total Cost |
|---|---|---|
| 5s | 5 × $0.18 | $0.90 |
| 10s | 10 × $0.18 | $1.80 |
| 30s | 30 × $0.18 | $5.40 |
Best Use Cases
- Object Removal — Remove unwanted people, objects, or distractions from footage.
- Environment Changes — Transform backgrounds, skies, or settings without reshooting.
- Style Transfer — Apply artistic styles, color grades, or visual aesthetics to existing videos.
- Visual Effects — Add weather effects, lighting changes, or atmospheric modifications.
- Content Repurposing — Adapt existing footage for new contexts or creative directions.
Example Prompts
- “Remove people from the video”
- “Change the background to a tropical beach”
- “Make it look like a vintage film from the 1970s”
- “Add snow falling throughout the scene”
- “Transform into an anime style”
- “Replace the sky with a dramatic sunset”
Pro Tips for Best Results
- Be specific and clear in your prompts — describe exactly what you want changed and how.
- Use the Prompt Enhancer to improve vague or simple instructions.
- For style changes, provide a reference image that captures the target aesthetic.
- Start with shorter clips to test your prompt before processing longer videos.
- Combine object removal with style changes in a single prompt for complex edits.
Notes
- If using URLs for video or reference image, ensure they are publicly accessible. A preview in the interface confirms successful loading.
- Processing time scales with video duration and complexity of the requested edit.
- Complex transformations may require more descriptive prompts for best results.
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/runwayml/gen4-aleph" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"aspect_ratio": "16:9"
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${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. | |
| video | string | Yes | - | Input video to generate from. Videos must be less than 16MB. Only 5s of the input video will be used. | |
| aspect_ratio | string | No | 16:9 | 16:9, 4:3, 1:1, 3:4, 9:16 | The aspect ratio of the generated media. |
| reference_image | string | No | - | - | Reference image to influence the style or content of the output |
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 |