Molmo2 Video Content Moderator

Playground

Molmo2-4B Video Content Moderator analyzes video content for safety, appropriateness, and policy compliance. Detects violence, nudity, gore, and other harmful visual content in videos using an open-source vision-language model. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Features

Molmo2 Video Content Moderator

Automatically screen videos for harmful content with Molmo2 Video Content Moderator. This AI-powered moderation tool analyzes videos and returns safety classifications for harassment, hate speech, sexual content, and violence — essential for content platforms, user-generated content, and compliance workflows.

Need image moderation? Try Molmo2 Image Content Moderator for image analysis.

Why It Works Great

Comprehensive detection: Screens for harassment, hate, sexual content, and violence.
Child safety: Dedicated detection for content involving minors.
Fast processing: Quick analysis with results in seconds.
JSON output: Clean, structured results for easy integration.
Ultra-affordable: Just $0.003 per video — 333 videos for $1.
Custom criteria: Optional text input for additional context.

Parameters

Parameter	Required	Description
video	Yes	Video to analyze (upload or public URL).
text	No	Optional context or custom moderation criteria.

How to Use

Upload your video — drag and drop or paste a public URL.
Add context (optional) — provide additional text for custom criteria.
Run — click the button to analyze.
Review results — check the JSON output for safety classifications.

Pricing

Flat rate per video analyzed.

Output	Cost
Per video	$0.003
100 videos	$0.30
1,000 videos	$3.00

Output Format

The model returns a JSON object with boolean flags for each content category:

&#123;
  "harassment": false,
  "hate": false,
  "sexual": false,
  "sexual/minors": false,
  "violence": false
&#125;

Detection Categories

Category	Description
harassment	Bullying, intimidation, or targeted abuse
hate	Hate speech, discrimination, or prejudice
sexual	Adult sexual content or nudity
sexual/minors	Any sexual content involving minors
violence	Graphic violence, gore, or harmful acts

Best Use Cases

Content Platforms — Screen user-uploaded videos before publishing.
Social Media — Moderate video content at scale.
E-commerce — Review product videos for policy compliance.
Education — Ensure learning content is age-appropriate.
Compliance — Meet content moderation requirements efficiently.
Pre-screening — Filter content before human review.

Pro Tips for Best Results

Use as a first-pass filter before human moderation for edge cases.
Integrate via API for automated moderation pipelines.
At $0.003 per video, batch processing is extremely cost-effective.
Combine with image moderation for comprehensive content screening.
Use the text parameter to provide context for borderline content.

Notes

If using a URL, ensure it is publicly accessible.
Processing time scales with video length.
Returns boolean values — true indicates detected content.
Designed for automated workflows with JSON output.
Consider human review for flagged content or edge cases.

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-content-moderator" \
--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		-	Video URL to moderate and analyze for safety compliance. Supports MP4, MOV, WebM formats.
text	string	No	-	-	Optional text prompt or question about the video content for contextual analysis.

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 moderation results with safety scores and detected visual categories across video frames.
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

Molmo2 Video Captioner Molmo2 Video Qa