Molmo2 Video Qa
Playground
Try it on WavespeedAI!Molmo2-4B Video QA: Answer questions about video content with temporal understanding. Open-source vision-language model. Ready-to-use REST API, no cold starts, duration-based pricing.
Features
Molmo2 Video QA
Molmo2 Video QA is a powerful video understanding model that answers questions about video content. Simply upload a video and ask anything — the model analyzes visual scenes, actions, objects, and context to deliver accurate, natural-language responses.
Built for developers and creators who need intelligent video comprehension without building complex pipelines.
Why Choose This?
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Natural language understanding Ask questions in plain English about what happens in your video — no need for timestamps or frame-by-frame annotation.
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Scene and action recognition Understands objects, people, movements, environments, and temporal sequences across the video.
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Flexible video input Accepts video uploads or public URLs for seamless integration into existing workflows.
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Fast and accurate Optimized for quick turnaround while maintaining high comprehension accuracy.
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Production-ready API Ready-to-use REST endpoint with predictable per-second pricing and no cold starts.
How to Use
- Upload your video — drag and drop a file or paste a public video URL.
- Write your question — describe what you want to know about the video content.
- Submit — the model processes the video and returns a natural-language answer.
- Iterate — ask follow-up questions or upload new videos as needed.
Pricing
Per-5-second billing with a 5-second minimum.
| Video Duration | Cost |
|---|---|
| Up to 5s | $0.005 |
| 10s | $0.01 |
| 30s | $0.03 |
| 60s | $0.06 |
| 120s (max) | $0.12 |
Billing Rules
- Minimum charge: 5 seconds ($0.005)
- Rate: $0.001 per second ($0.005 per 5 seconds)
- Maximum video length: 120 seconds (2 minutes)
Best Use Cases
- Content moderation — Automatically review video uploads for policy compliance.
- Video search and indexing — Extract semantic information for searchable video libraries.
- Accessibility — Generate descriptions of video content for visually impaired users.
- Education and training — Analyze instructional videos and answer learner questions.
- Surveillance and monitoring — Summarize events or detect specific actions in footage.
- Social media analytics — Understand trends and content themes across video posts.
Notes
- If using a URL, ensure it is publicly accessible. A preview thumbnail in the interface confirms successful access.
- For videos longer than 2 minutes, split into segments and process separately.
- Clear, well-lit footage with minimal background noise yields the best results.
- Be specific in your questions for more precise answers.
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/molmo2/video-qa" \
--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 |
|---|---|---|---|---|---|
| video | string | Yes | - | Input video URL for question answering. Supports common video formats (MP4, MOV, WebM). Maximum 2 minutes. | |
| text | string | Yes | - | - | Your question about the video content. |
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 |