Minimax Video 01
Playground
Try it on WavespeedAI!Minimax Video-01 is a text-to-video model offering high compression, strong text responsiveness, cinematic styles, and native HD output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
MiniMax Video-01 — minimax/video-01
MiniMax Video-01 is a text-to-video (T2V) model for generating short, coherent clips from a single prompt. It’s built for cinematic pacing, stable scene continuity, and prompt-faithful motion, making it a strong default for story beats, product shots, and concept trailers.
What it’s good at
- Text-to-Video (T2V): generate a complete clip from a prompt
- Cinematic language: responds well to shot descriptions and camera cues
- Coherent motion: maintains continuity across frames for simple-to-moderate action
- Fast iteration: great for rapid creative exploration and storyboard-style outputs
Inputs
- Prompt (required): describe subject, action, environment, lighting, camera, and style
- Image (optional, if supported in your deployment): provide a reference frame to steer the look
- Enable prompt expansion (optional): automatically expands/optimizes your prompt for better visual quality
Key parameters
-
enable_prompt_expansion:
- On: better visual richness and fewer “under-specified” results
- Off: tighter control, closer to your exact wording (often best for structured prompts)
Prompting tips
-
Use a “director brief” structure:
- Subject: who/what is on screen
- Action: what changes over time
- Scene: where + time of day + lighting
- Camera: framing + movement + transitions
- Style: mood + medium + references (optional)
-
Prefer one clear main action per clip (then iterate).
-
If you need stronger motion, add pace and intent: slowly, rapidly, abrupt cut, smooth dolly-in, handheld shake.
Use cases
- Concept trailers & story beats: quick visual drafts for narrative sequences
- Marketing clips: product mood videos and brand-style visuals
- Social content: punchy short clips with strong camera direction
- Pre-visualization: test shots, lighting, and staging before production
Pricing
| Model | Price per video |
|---|---|
| minimax/video-01 | $0.50 |
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/minimax/video-01" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"enable_prompt_expansion": true
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${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 | No | - | The model generates video with the picture passed in as the first frame.Base64 encoded strings in data:image/jpeg; base64,{data} format for incoming images, or URLs accessible via the public network. The uploaded image needs to meet the following conditions: Format is JPG/JPEG/PNG; The aspect ratio is greater than 2:5 and less than 5:2; Short side pixels greater than 300px; The image file size cannot exceed 20MB. | |
| enable_prompt_expansion | boolean | No | true | - | The model automatically optimizes incoming prompts to improve build quality. |
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 |