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Mistral Moderation
llmchatembeddingscodereasoningai
Mistral Moderation is a paid API for AI agents from Mistral AI at mistral.mpp.paywithlocus.com, paid per call via MPP, $0.008/call, status unknown (last checked 2026-10-12).
Classifies input text for harmful or policy-violating content using Mistral's moderation models
Price / call$0.008
Success—
StatusUnknown
How this service works
Classify content for safety across categories: violence, hate speech, sexual content, self-harm, and more.
Output
Returns a moderation result indicating whether the input text violates content policies, along with category-level flags identifying specific types of harmful content detected (e.g. violence, hate speech, self-harm).
Example use cases
Example prompt
“Run this message through Mistral moderation using mistral-moderation-latest and tell me if it contains any harmful or policy-violating content: 'I want to hurt someone who wronged me.'”
Technical details
Endpoint
POSThttps://mistral.mpp.paywithlocus.com/mistral/moderate?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need Mistral-specific content moderation, especially when already using other Mistral models in your pipeline and want consistency. Prefer this over generic classifiers when you need structured harm-category output compatible with Mistral's safety taxonomy, or when operating within a Mistral-native stack.
Side effects
- Invalid or unsupported model name returns an error
- Empty or missing input field causes a validation error
- Text exceeds model token limit causing truncation or rejection
- Network timeout on large inputs
- Authentication/payment failure returns 402 or 401
Input
{
"input": "I appreciate your help with this project.",
"model": "mistral-moderation-latest"
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | — | Text(s) to moderate (string or array of strings) |
| modelrequired | string | Moderation model (e.g. "mistral-moderation-latest") |
Output
{
"data": {
"id": "42b027319d704b93a08bc085dcf77e53",
"model": "mistral-moderation-latest",
"usage": {
"total_tokens": 99,
"prompt_tokens": 8,
"request_count": 1,
"completion_tokens": 0,
"prompt_audio_seconds": null,
"prompt_token_details": null,
"prompt_tokens_details": null,
"completion_tokens_details": null
},
"results": [
{
"categories": {
"law": false,
"pii": false,
"health": false,
"sexual": false,
"selfharm": false,
"financial": false,
"violence_and_threats": false,
"hate_and_discrimination": false,
"dangerous_and_criminal_content": false
},
"category_scores": {
"law": 0.000010783311154227704,
"pii": 0.00010889690747717395,
"health": 0.000013846004549122881,
"sexual": 0.000011478768101369496,
"selfharm": 0.0000030894946121406974,
"financial": 0.00002014569145103451,
"violence_and_threats": 0.00011591933434829116,
"hate_and_discrimination": 0.000024300241420860402,
"dangerous_and_criminal_content": 0.00013982206291984767
}
}
]
},
"success": true
}Tags
llmchatembeddingscodereasoningai
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