Molmo2-4B Text Content Moderator: Analyze text content for safety, appropriateness, and policy compliance. Detects hate speech, violence, sexual content, and other harmful categories. Open-source vision-language model. Ready-to-use REST API, no cold starts, affordable pricing.
Idle
{
"hate": false,
"sexual": false,
"violence": false,
"harassment": false,
"sexual/minors": false
}$0.003per run·~333 / $1
Automatically screen text for harmful content with Molmo2 Text Content Moderator. This AI-powered moderation tool analyzes text and returns safety classifications for harassment, hate speech, sexual content, and violence — essential for chat platforms, user-generated content, and compliance workflows.
| Parameter | Required | Description |
|---|---|---|
| text | Yes | Text content to analyze for harmful content. |
Flat rate per text analyzed.
| Output | Cost |
|---|---|
| Per request | $0.003 |
| 100 requests | $0.30 |
| 1,000 requests | $3.00 |
The model returns a JSON object with boolean flags for each content category:
{
"harassment": false,
"hate": false,
"sexual": false,
"sexual/minors": false,
"violence": false
}
| Category | Description |
|---|---|
| harassment | Bullying, intimidation, or targeted abuse |
| hate | Hate speech, discrimination, or prejudice |
| sexual | Adult sexual content or explicit language |
| sexual/minors | Any sexual content involving minors |
| violence | Threats, graphic violence descriptions, or harmful content |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/molmo2/text-content-moderator with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Molmo2 Text Content Moderator below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/molmo2/text-content-moderator" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"enable_sync_mode": false
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/molmo2/text-content-moderator", {
"enable_sync_mode": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/molmo2/text-content-moderator",
{
"enable_sync_mode": false
}
)
print(output["outputs"][0]) # → URL of the generated outputMolmo2 Text Content Moderator is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Molmo2-4B Text Content Moderator: Analyze text content for safety, appropriateness, and policy compliance. Detects hate speech, violence, sexual content, and other harmful categories. Open-source vision-language model. Ready-to-use REST API, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/molmo2-text-content-moderator.
Molmo2 Text Content Moderator starts at $0.003 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `enable_sync_mode`, `text`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/molmo2-text-content-moderator.
Average end-to-end generation time on WaveSpeedAI is around 2 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.