Name: Qwen3-VL 8B Instruct API: Image and Video Understanding
Brand: magicapi
SKU: api-magicapi-vision-language-model-api-lucataco-qwen3-vl-8b-instruct
Availability: InStock
Author: API Market

Shashank Agarwal

# 👁️ Image and Video Understanding API (Alibaba Qwen Qwen3-VL 8B Instruct)

## Overview
Qwen3-VL 8B Instruct is a vision-language model in Alibaba's Qwen series. It reads an image or a video together with a text instruction and answers in text.

Send a `prompt` and, optionally, one `media` file: an image (jpg, png and similar) or a video (mp4, avi, mov and similar). For videos, `video_fps` sets how many frames per second are sampled and `video_max_pixels` caps the size of each frame. Without media the model answers the prompt as text only. The answer comes back as one string.

## Features
- **Images and videos**: one `media` URL per request, image or video.
- **Video sampling**: `video_fps` (0.1 to 10, default 1) frames per second; lower values reduce the token count.
- **Frame size cap**: `video_max_pixels` (0 to 1048576, default 200704; 0 means auto). The model's own recommendation is 50176 to 786432.
- **Answer length cap**: `max_new_tokens` from 1 to 4096 (default 512).
- **Sampling controls**: `temperature` 0 to 2 (default 0.7; 0 is deterministic) and `top_p` 0 to 1 (default 0.9).

## Use Cases
1. **Video summaries**: describe what happens in a short clip.
2. **Image questions**: describe a photo, read a chart or answer questions about a screenshot.
3. **Content tagging**: produce descriptions for search and cataloguing of images and clips.
4. **Accessibility**: generate text descriptions of visual media.

## Visual Examples
### Example Input
Video: [Watch the input video](https://blog.api.market/wp-content/uploads/2026/10/qwen3-vl-8b-instruct-input-api-market.mp4)

Prompt: "What is happening in this video?"

Settings: `video_fps` 1, `video_max_pixels` 200704, `max_new_tokens` 512, `temperature` 0.7, `top_p` 0.9.

### Example Output
```text
In the video, a monkey is seen riding a skateboard down a sidewalk in a park. The monkey is wearing sunglasses and appears to be enjoying the ride. The camera follows the monkey as it moves down the sidewalk, passing by people sitting on benches and enjoying the sunny day. The monkey continues to ride until it reaches the end of the sidewalk, where it stops and looks around. The video ends with the monkey standing still, looking at the camera.
```

## Input Parameters
| Field | Type | Required | Default | Allowed values | Description |
| --- | --- | --- | --- | --- | --- |
| `max_new_tokens` | integer | No | `512` | 1 to 4096 | Maximum number of new tokens to generate |
| `media` | string (URL) | No | none |  | Optional image or video URL. Images: jpg, png and similar. Videos: mp4, avi, mov and similar. |
| `prompt` | string | No | `Describe what is happening in the media content` |  | Instruction or question for the model |
| `temperature` | number | No | `0.7` | 0 to 2 | Sampling temperature; set to 0 for deterministic output |
| `top_p` | number | No | `0.9` | 0 to 1 | Cumulative probability for nucleus sampling |
| `video_fps` | number | No | `1` | 0.1 to 10 | Frames per second sampled from a video. Only applies to video inputs. Lower values reduce the token count. |
| `video_max_pixels` | integer | No | `200704` | 0 to 1048576 | Maximum pixels per video frame. Only applies to video inputs. Set to 0 for auto. Recommended: 50176 to 786432. |

## Pricing
- **Pay As You Go (PAYG) pricing**: you only pay for what you use.
- **Price**: $0.0067 per API unit.
- **1 API unit = 1 request with up to 6 seconds of processing.** A request that takes longer is billed one more unit for each started 6-second block of processing time.
- **Example cost**: the example request above took 5.93 seconds of processing, which is 1 started 6-second block, so it cost 1 unit = $0.0067.
- Longer videos, a higher `video_fps`, larger frames and longer answers take longer and can use more units.
- **Failed or cancelled predictions are not billed.**
- **GET requests to check prediction status** are free and don't count toward API unit usage.
- **No monthly subscription fee.**

## API Documentation

### Base URL
All API requests go to: `https://prod.api.market/api/v1/magicapi/vision-language-model-api-lucataco-qwen3-vl-8b-instruct`

### Authentication
Send your api.market API key in the `x-api-market-key` header:
```
x-api-market-key: YOUR_API_MARKET_KEY
```

### Asynchronous Processing
**IMPORTANT**: This API is asynchronous. The flow is:
1. Send a POST request to `/predictions`. A successful request returns **201 Created** with a prediction `id` and a `status` of `starting` or `processing`.
2. Poll GET `/predictions/{id}` with that ID.
3. Keep polling while `status` is `starting` or `processing`.
4. Stop when `status` is `succeeded` (read `output`), `failed` or `canceled` (read `error`).

A polling interval of 1 second and an overall timeout of 600 seconds (10 minutes) work well.

### Endpoints

#### Create a Prediction
```bash
curl -X POST "https://prod.api.market/api/v1/magicapi/vision-language-model-api-lucataco-qwen3-vl-8b-instruct/predictions" \
  -H "Content-Type: application/json" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY" \
  -d '{
    "version": "39e893666996acf464cff75688ad49ac95ef54e9f1c688fbc677330acc478e11",
    "input": {
      "media": "https://blog.api.market/wp-content/uploads/2026/10/qwen3-vl-8b-instruct-input-api-market.mp4",
      "top_p": 0.9,
      "prompt": "What is happening in this video?",
      "video_fps": 1,
      "temperature": 0.7,
      "max_new_tokens": 512,
      "video_max_pixels": 200704
    }
  }'
```

Response (201 Created):
```json
{
  "id": "3yagw9x7h1rmy0d1d12v1bd34g",
  "version": "39e893666996acf464cff75688ad49ac95ef54e9f1c688fbc677330acc478e11",
  "status": "starting",
  "created_at": "2026-10-23T10:19:17.923Z"
}
```

#### Check Prediction Status
```bash
curl -X GET "https://prod.api.market/api/v1/magicapi/vision-language-model-api-lucataco-qwen3-vl-8b-instruct/predictions/{id}" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY"
```

Response when the prediction has finished (200 OK):
```json
{
  "id": "3yagw9x7h1rmy0d1d12v1bd34g",
  "status": "succeeded",
  "output": "In the video, a monkey is seen riding a skateboard down a sidewalk in a park. The monkey is wearing sunglasses and appears to be enjoying the ride. The camera follows the monkey as it moves down the sidewalk, passing by people sitting on benches and enjoying the sunny day. The monkey continues to ride until it reaches the end of the sidewalk, where it stops and looks around. The video ends with the monkey standing still, looking at the camera.",
  "error": null,
  "created_at": "2026-10-23T10:19:17.923Z",
  "started_at": "2026-10-23T10:19:17.937Z",
  "completed_at": "2026-10-23T10:19:23.871Z"
}
```

`output` is one string with the model's answer.

### Status Codes
- **201 Created**: prediction created (POST `/predictions`). This is the normal success response.
- **200 OK**: prediction details returned (GET `/predictions/{id}`).
- **400 Bad Request**: invalid input, for example a `video_fps` above 10 or a `max_new_tokens` above 4096.
- **401 Unauthorized**: missing or invalid API key.
- **404 Not Found**: no prediction with that ID.
- **429 Too Many Requests**: rate limit exceeded.
- **500 Internal Server Error** or **503 Service Unavailable**: temporary server problem; retry later.

## Rate Limits
All plans allow 10 requests per second. Requests above that return `429 Too Many Requests`; back off before retrying and honour any `Retry-After` header. Polling a prediction with GET is free but still counts toward the per-second limit, so poll every 1 to 5 seconds rather than in a tight loop.

## Error Handling
- Check the HTTP status code of every request and read the response body for the error message.
- A prediction can also end with `status` set to `failed`; the `error` field then explains why. Failed predictions are not billed.
- Retry 429, 500 and 503 responses with exponential backoff. Fix the input before retrying a 400.

## Implementation Guide
### Example Code

#### JavaScript
```javascript
const apiKey = "YOUR_API_MARKET_KEY";
const baseUrl = "https://prod.api.market/api/v1/magicapi/vision-language-model-api-lucataco-qwen3-vl-8b-instruct";

async function createAndWaitForPrediction(input) {
  const response = await fetch(`${baseUrl}/predictions`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      "x-api-market-key": apiKey
    },
    body: JSON.stringify({ version: "39e893666996acf464cff75688ad49ac95ef54e9f1c688fbc677330acc478e11", input })
  });

  if (response.status !== 201) {
    throw new Error(`API error: ${response.status} ${await response.text()}`);
  }

  const prediction = await response.json();
  return pollForResults(prediction.id);
}

const delay = (ms) => new Promise((resolve) => setTimeout(resolve, ms));

async function pollForResults(predictionId) {
  const maxTimeout = 600000;
  const pollInterval = 1000;
  const startTime = Date.now();

  while (Date.now() - startTime < maxTimeout) {
    const response = await fetch(`${baseUrl}/predictions/${predictionId}`, {
      headers: { "x-api-market-key": apiKey }
    });

    if (!response.ok) {
      throw new Error(`API error: ${response.status} ${await response.text()}`);
    }

    const prediction = await response.json();

    if (prediction.status === "succeeded") {
      return prediction.output;
    }

    if (prediction.status === "failed" || prediction.status === "canceled") {
      throw new Error(`Prediction ${prediction.status}: ${prediction.error || "Unknown error"}`);
    }

    await delay(pollInterval);
  }

  throw new Error("Prediction timed out after 10 minutes");
}

createAndWaitForPrediction({
    "media": "https://blog.api.market/wp-content/uploads/2026/10/qwen3-vl-8b-instruct-input-api-market.mp4",
    "top_p": 0.9,
    "prompt": "What is happening in this video?",
    "video_fps": 1,
    "temperature": 0.7,
    "max_new_tokens": 512,
    "video_max_pixels": 200704
  }).then((output) => console.log(output));
```

#### Python
```python
import time
import requests

API_KEY = "YOUR_API_MARKET_KEY"
BASE_URL = "https://prod.api.market/api/v1/magicapi/vision-language-model-api-lucataco-qwen3-vl-8b-instruct"


def create_and_wait_for_prediction(input_data):
    headers = {"Content-Type": "application/json", "x-api-market-key": API_KEY}
    response = requests.post(
        f"{BASE_URL}/predictions",
        headers=headers,
        json={"version": "39e893666996acf464cff75688ad49ac95ef54e9f1c688fbc677330acc478e11", "input": input_data},
    )

    if response.status_code != 201:
        raise Exception(f"API error: {response.status_code} {response.text}")

    return poll_for_results(response.json()["id"])


def poll_for_results(prediction_id):
    max_timeout = 600
    poll_interval = 1
    headers = {"x-api-market-key": API_KEY}
    start_time = time.time()

    while time.time() - start_time < max_timeout:
        response = requests.get(f"{BASE_URL}/predictions/{prediction_id}", headers=headers)

        if response.status_code != 200:
            raise Exception(f"API error: {response.status_code} {response.text}")

        prediction = response.json()

        if prediction["status"] == "succeeded":
            return prediction["output"]

        if prediction["status"] in ("failed", "canceled"):
            raise Exception(f"Prediction {prediction['status']}: {prediction.get('error') or 'Unknown error'}")

        time.sleep(poll_interval)

    raise Exception("Prediction timed out after 10 minutes")


print(create_and_wait_for_prediction({
    "media": "https://blog.api.market/wp-content/uploads/2026/10/qwen3-vl-8b-instruct-input-api-market.mp4",
    "top_p": 0.9,
    "prompt": "What is happening in this video?",
    "video_fps": 1,
    "temperature": 0.7,
    "max_new_tokens": 512,
    "video_max_pixels": 200704
}))
```

## FAQ
- **Can I send an image instead of a video?**
  - Yes. `media` accepts an image or a video. `video_fps` and `video_max_pixels` only apply to videos.
- **Can I send several files in one request?**
  - No. Each request takes one `media` file.
- **How do I make long videos cheaper?**
  - Lower `video_fps` and `video_max_pixels`. Fewer and smaller frames mean fewer tokens and less processing time.
- **Do I have to send media?**
  - No. Without `media` the model answers the text prompt alone.
- **How long can an answer be?**
  - Up to 4096 new tokens, set with `max_new_tokens` (default 512).

## Contact Us
If you have any questions, reach out to us through the chat on the bottom right of the page. You can also email our support team at hello@magicapi.com.


Send an image or a video with a question to Qwen3-VL 8B Instruct and get a text answer, with control over video frame rate and frame size.