OpenAI Moderation API Pricing: Free, Rate Limits, and Alternatives

That does not make the decision finished. Production teams still need to understand what the endpoint covers, what it does not cover, how rate limits apply, and when a paid or platform-integrated moderation workflow is easier to operate.

This guide separates the official pricing answer from the practical engineering decision.

TL;DR

• OpenAI's Moderation endpoint is free for OpenAI API users, according to OpenAI's Help Center.
• OpenAI's omni-moderation-latest model is designed to detect harmful content and accepts text and images as input, according to the official OpenAI model page.
• Free pricing does not remove workflow costs such as logging, review queues, policy mapping, retries, fallback behavior, and application-specific decisions.
• Choose OpenAI's free endpoint if you already use OpenAI directly and your moderation workflow fits its categories and response format.
• Consider an OpenAI-compatible moderation API like EvoLink Moderation 1.0 if you want text and image checks, risk_level summaries, flat per-call pricing, and the moderation workflow inside your EvoLink API stack.

Is the OpenAI Moderation API free?

Yes. OpenAI's official Help Center states that the Moderation endpoint is free for OpenAI API users and that usage of the tool does not count toward monthly usage limits.

That is the pricing answer. The next question is operational:

For prototypes, internal tools, and simple text-first moderation, it may be. For applications that handle user-generated content, image uploads, AI agents, or review queues, the API call is only one part of the system.

What does OpenAI moderation cover?

That means teams should read the category table carefully before assuming that every text category maps directly to image moderation.

The real cost is workflow, not just API pricing

The Moderation endpoint may be free, but a production moderation system still needs decisions around:

• where to run checks: before model calls, after model responses, or both
• how to map categories to allow, review, or block decisions
• how to log moderation outcomes without storing sensitive content unnecessarily
• how to handle false positives and appeals
• how to moderate image uploads separately from text input
• how to monitor latency, errors, and rate limits
• how to keep policy behavior consistent across product surfaces

Those are engineering and operations costs. They do not show up on a pricing page, but they decide whether the moderation layer is actually maintainable.

When OpenAI's free endpoint is a good fit

OpenAI's free Moderation endpoint is often a good first choice when:

• you already use OpenAI directly
• your app is mostly text-first
• you only need OpenAI's documented moderation categories
• you can build your own review and escalation workflow
• your team is comfortable owning response parsing, thresholds, and logs

In that case, the free endpoint is hard to argue against. Start there, test it against your real content, and measure false positives and missed cases before routing production traffic.

When an OpenAI-compatible alternative makes sense

EvoLink Moderation 1.0 is useful when you want:

• text-only, image-only, and text-plus-image checks through one endpoint
• 13 harm categories with per-category scores
• an evolink_summary object with risk_level, flagged, violations, max_score, and max_category
• flat per-call pricing instead of token math
• a response shape that is easier to map to allow, review, or block logic

How to use OpenAI Moderation API in Python

If you are already using the OpenAI SDK, a basic text moderation call looks like this:

from openai import OpenAI

client = OpenAI()

response = client.moderations.create(
    model="omni-moderation-latest",
    input="user text here"
)

print(response.results[0].flagged)
print(response.results[0].categories)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_EVOLINK_API_KEY",
    base_url="https://direct.evolink.ai/v1"
)

response = client.moderations.create(
    model="evolink-moderation-1.0",
    input="user text here"
)

summary = response.model_extra["evolink_summary"]
print(summary["risk_level"])
print(summary["violations"])

OpenAI vs EvoLink: pricing and workflow comparison

This is not a universal winner comparison. OpenAI's endpoint is the obvious fit for many OpenAI-native applications. EvoLink is a better fit when your moderation workflow benefits from a unified text and image endpoint, a simplified risk summary, and EvoLink-based billing and operations.

Practical recommendation

Use OpenAI's free Moderation endpoint if your application is already OpenAI-native and your moderation policy maps cleanly to its documented categories.

Use a multi-layered moderation system if your application has custom policy requirements that need brand rules, human review, appeals, or compliance workflows beyond any single moderation API.

FAQ

Is the OpenAI Moderation API free?

Yes. OpenAI's Help Center says the Moderation endpoint is free for OpenAI API users and does not count toward monthly usage limits.

Does OpenAI moderation support images?

Is EvoLink Moderation cheaper than OpenAI Moderation?

Can I use EvoLink Moderation as an OpenAI Moderation API alternative?

Should I moderate prompts, outputs, or both?

For production AI applications, many teams moderate both inputs and outputs. Input moderation can reduce unsafe requests before they reach a model. Output moderation can catch unsafe generated responses before they reach users.

What is omni-moderation-latest?

What is the OpenAI Moderation API rate limit?

How do I use the OpenAI Moderation API in Python?

Related moderation guides

• omni-moderation-latest Explained: OpenAI Moderation API Guide
• Best Content Moderation APIs and Tools for Developers
• Image Moderation API Guide: How to Filter Unsafe User-Uploaded Images
• How to Add Content Moderation to Your Chatbot or AI Agent