# PixVerse V5 Text-to-Video

> Generate a short, cinematic video from a text prompt, with selectable aspect ratio, resolution, duration, and optional style presets.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/pixverse/v5/text-to-video`
- **Model ID**: `pixverse/v5/text-to-video`
- **Category**: text-to-video
- **Kind**: inference
- **Tags**: pixverse, pixverse-v5, text-to-video, video-generation, cinematic, animation

## Pricing

- **Price**: $0.2 per output

## Request Lifecycle

This model runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps:

1. **Submit** — `POST https://queue.modelrunner.run/pixverse/v5/text-to-video` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the model; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>` (exact key=value matches, AND-ed). The response carries request handles only (no output yet):

```json
{
  "status": "IN_QUEUE",
  "request_id": "<21-char id>",
  "status_url": "https://queue.modelrunner.run/pixverse/v5/text-to-video/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/pixverse/v5/text-to-video/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/pixverse/v5/text-to-video/requests/<request_id>/cancel"
}
```

2. **Poll status** — `GET <status_url>` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field.

3. **Read result** — `GET <response_url>`. Returns the finished request, including the generated `output`:

```json
{ "id": "<request_id>", "status": "COMPLETED", "output": ..., "input": ... }
```

The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow.

### Input Schema

- **`seed`** (`integer | null`, _optional_):
  Random seed for reproducible generation. Leave unset for a random result.

- **`style`** (`StyleEnum | null`, _optional_):
  Optional stylized look applied to the whole clip. Leave unset for a natural render.
  - Options: `"anime"`, `"3d_animation"`, `"clay"`, `"comic"`, `"cyberpunk"`

- **`prompt`** (`string`, _required_):
  Text description of the video to generate.

- **`duration`** (`DurationEnum`, _optional_):
  Length of the generated video in seconds. 8-second clips cost more than 5-second clips.
  - Default: `"5"`
  - Options: `"5"`, `"8"`

- **`resolution`** (`ResolutionEnum`, _optional_):
  The resolution of the generated video. Higher resolutions cost more.
  - Default: `"720p"`
  - Options: `"360p"`, `"540p"`, `"720p"`, `"1080p"`

- **`aspect_ratio`** (`AspectRatioEnum`, _optional_):
  The aspect ratio of the generated video frame.
  - Default: `"16:9"`
  - Options: `"16:9"`, `"4:3"`, `"1:1"`, `"3:4"`, `"9:16"`

- **`negative_prompt`** (`string`, _optional_):
  Describe content to avoid in the generated video.
  - Default: `""`

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "prompt": "Cinematic aerial shot flying over a misty pine forest at dawn, golden sunlight breaking through the fog, smooth drone motion.",
  "duration": "5",
  "resolution": "540p",
  "aspect_ratio": "16:9",
  "negative_prompt": ""
}
```

**Output**

```json
"https://media.modelrunner.ai/m3rLnnXAO4kraJhhEmP2c.mp4"
```
## Usage Examples

### cURL

The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`.

```bash
# 1. Submit the request (returns request handles, not the output)
SUBMIT=$(curl --silent --request POST \
  --url https://queue.modelrunner.run/pixverse/v5/text-to-video \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "prompt": "Cinematic aerial shot flying over a misty pine forest at dawn, golden sunlight breaking through the fog, smooth drone motion.",
  "duration": "5",
  "resolution": "540p",
  "aspect_ratio": "16:9",
  "negative_prompt": ""
}')

STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url')
RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url')

# 2. Poll until the request leaves the queue / in-progress state
while true; do
  STATUS=$(curl --silent --url "$STATUS_URL" \
    --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status')
  echo "Status: $STATUS"
  case "$STATUS" in
    COMPLETED) break ;;
    FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;;
  esac
  sleep 1
done

# 3. Read the finished request, including the generated output
curl --silent --url "$RESPONSE_URL" \
  --header "Authorization: Key $MODEL_RUNNER_KEY"
```

### JavaScript

```javascript
import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("pixverse/v5/text-to-video", {
  input: {
  "prompt": "Cinematic aerial shot flying over a misty pine forest at dawn, golden sunlight breaking through the fog, smooth drone motion.",
  "duration": "5",
  "resolution": "540p",
  "aspect_ratio": "16:9",
  "negative_prompt": ""
}
});

console.log(result.data);
```

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "pixverse/v5/text-to-video",
        arguments={
  "prompt": "Cinematic aerial shot flying over a misty pine forest at dawn, golden sunlight breaking through the fog, smooth drone motion.",
  "duration": "5",
  "resolution": "540p",
  "aspect_ratio": "16:9",
  "negative_prompt": ""
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/models/pixverse/v5/text-to-video)
- [OpenAPI Schema](https://modelrunner.ai/models/pixverse/v5/text-to-video/openapi.json)
- [LLM Instructions](https://modelrunner.ai/models/pixverse/v5/text-to-video/llms.txt)