- Developers & Platform Owners: Implement scalable, multilingual guardrails across apps, chatbots, forums, or user-generated content pipelines.
- Chat & Conversational AI Builders: Use the conversational endpoint for context-aware filtering of back-and-forth dialogues.
- Global Enterprises: Enforce compliance in 11 supported languages (e.g., Arabic, Chinese, English, French, German, Japanese, Korean, Portuguese, Russian, Spanish, Italian).
- Content Moderation Teams: Leverage raw scores to customize thresholds and fine-tune precision-recall balance for each category.
- Regulated Industries: Detect model-generated advice and PII to ensure safety and compliance in sensitive sectors.
How to Use Mistral Moderation API?
- Choose Endpoint: Use `classifiers.moderate` for raw text or `classifiers.moderate_chat` for conversational turns.
- Send Payload: Provide inputs as strings (raw) or conversation arrays (conversational endpoint) to Mistral’s Python, TypeScript, or cURL clients.
- Receive Category Scores: The API returns boolean flags and confidence scores for each category (e.g., `‘violenceandthreats’: true, score 0.999`).
- Adjust Policy Thresholds: Use raw scores to tailor sensitivity per use case, or rely on default thresholds (precision 0.8–0.9, recall 0.7–0.99).
- Scale Safely: Use batch endpoint to reduce latency and cost (~25% savings for high-volume requests).
- Multilingual by Design: Supports 11 major languages beyond English, a key advantage over many moderation APIs.
- Dual-Endpoint Support: Handles both raw text and conversational filtering with context awareness.
- Fine-Grained Risk Scoring: Provides category-level confidence scores empowering nuanced policy control.
- Industry-Grade Guardrails: Designed to filter model-generated advice, PII, and harmful claims to improve downstream safety.
- Batching for Efficiency: Built-in batch API reduces cost and improves scalability for high-volume moderation needs.
- Strong multilingual support in 11 languages
- Both raw-text and conversational moderation endpoints
- Category-level scoring enables customizable policy tuning
- Backed by Ministral 8B with robust safety precision/recall
- Batch endpoint reduces costs and improves throughput
- Being early-stage, benchmark comparisons to alternatives like OpenAI or Perspective are limited
- Potential bias and false positives (e.g., in AAVE or disability-related terms) may still exist
- Not yet as customizable as full on-prem policy engines
API only
$0.1 per 1M input tokens
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Editorial Note
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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