Hive Moderation review: strong on visual, narrower on community text
Bottom line: Hive is one of the strongest options for visual moderation: five visual category groups, video sampling, live stream support and audio, with severity levels on text. It is less of a fit if you want a quick self-serve API for community chat with labels like scams or self-harm, because text is capped at 1024 characters, there is no batch endpoint, and the docs tie text and visual moderation to annual contracts. Confirm pricing details with Hive.
This review uses Hive's own pricing page and docs, read on 26 October 2026. Where they conflict, we say so.
What Hive is
Hive sells several moderation products through one platform:
- Visual moderation classifies whole images or videos into classes with a confidence score for each.
- Text moderation returns a severity per class. Hive notes that its APIs do not remove content or ban users themselves.
- Audio moderation, plus classifiers for AI-generated content, listed on its pricing page.
- Hive VLM, a multimodal LLM you prompt with your own policy. The pricing page says it replaces Hive's other models for many customers.
What Hive does well
Visual coverage is deep. Hive groups visual classes into sexual content, violent imagery, drugs, hate imagery and image attributes, and offers brand safety classes aligned to GARM. Image formats include gif, jpg, png and webp, and video formats include mp4, webm, avi, mkv, wmv and mov.
Video and live streams. Videos are split into frames, by default one frame per second, and Hive can adjust the sampling rate. It also accepts live streams over RTMP and HLS. For platforms with live video, that matters.
Severity levels on text. Text classes are ordered from level 3 (most severe) to level 0 (benign). That gives you a built-in way to treat mild and severe content differently, rather than inventing your own thresholds.
Languages. Hive says it supports about 30 languages for text and that its models understand emojis. Coverage varies by class and language: its table marks some as beta and some as unsupported, and unsupported classes return a score of -1. That level of detail is useful when planning.
Flexible custom policy through the VLM. Because the VLM is driven by your prompt, you can describe a policy that the fixed classes do not cover. Hive's docs are clear that the prompt is the policy, so quality depends on how you write it.
An OpenAI-compatible interface for the VLM, so existing client libraries can talk to it.
Enterprise path. Higher limits, custom models and extra products such as CSAM detection are available through sales.
Where it runs out
Text limits. Text submissions are limited to 1024 characters, which Hive says is deliberate because longer text may introduce bias. Longer content has to be split by you.
No batch endpoint. Hive's FAQ says its APIs do not currently support batch processing.
Text labels are narrower for communities. The text heads in the classification docs are sexual, hate, violence, bullying, drugs (marked beta), child exploitation, gibberish, spam, promotions and phone numbers. Hive's other text page describes the text model as five main classes, so the two pages disagree on the count. Neither lists self-harm or scams.
Access is partly sales-gated. The pricing page shows self-serve plans with a limit of 100 requests a day on some products, and "Contact Sales" for higher limits. Video must be enabled through a contact form. The docs state that text and visual moderation require an annual contract, which we could not reconcile with the self-serve listing. Ask Hive what applies to you.
Rate limits depend on plan. Enterprise projects start at 25 to 50 tasks per second depending on the model, and the VLM starts at 5 requests per second. Higher throughput is by request.
No SDK in the docs we read. The docs show REST examples and an OpenAI-style client for the VLM, but we found no Hive-branded SDK package.
No conversation-context option that we could find. Text classification takes the message you send. We did not find a parameter for flagging that a message needs surrounding conversation.
Where Supervisor fills gaps, and where it does not
Supervisor is our product, so read this as a vendor's view.
| Hive | Supervisor | |
|---|---|---|
| Text labels | Severity-leveled classes: sexual, hate, violence, bullying, drugs, and others | 16 labels including self-harm, scam, spam, promotional, illegal |
| Context | Not found in the docs | include_context returns needs_context and context_labels |
| Implicit harm | Not found in the docs | implicit_labels |
| Batch | Not supported | Batch endpoint, half price for two or more |
| Models | Several products | Three tiers: Observer, Sentinel, Arbiter |
| Languages | About 30, coverage varies | Non-English translated before classification, including slang and mixed-language |
| Username check | Not found in the docs | Dedicated endpoint |
| SDKs | None found in the docs | Python, JavaScript, Go, Rust, Java |
| Live streams | RTMP and HLS | No live stream input in the API |
| Video | Frame sampling, sales-enabled | Up to 60 s and 10 MB, up to 20 frames |
| Audio | Yes | Not covered here |
| Severity levels | 0 to 3 on text | Labels and flags, not severity bands |
| Ready-made Discord bot | Not found in the docs | Yes |
| Pricing | Confirm with Hive | One plan, £13.99 a month |
For visual moderation at scale, live video and audio, Hive is the stronger option. For community text where scams, self-harm and conversation context matter, Supervisor covers more.
Who Hive is right for
- Platforms with heavy image, video or live stream moderation needs.
- Enterprises that want a sales-led relationship, custom models and support.
- Teams that want severity levels built into text results.
It is a weaker fit for small teams wanting a self-serve text API with broad community labels, or anyone who needs batch endpoints and long text without splitting.
Verdict
Hive is a serious visual moderation provider with sensible text severity levels. Its text side is more constrained and its access model is less clear from the outside. Many teams will want Hive for visual content and something else for chat. Test both on your own data.
Try your own messages in the live demo, read the API reference, or create a free account.