ImageDetector vs Hive: Image Detection Accuracy Compared
Hive is built for scale. ImageDetector is built for convenience. That sounds like a simple choice — until you look at how close performance can be. This article compares them the way most people actually use them.
John Angelo Yap
Updated February 25, 2026
Reading Time: 4 minutes
AI image detection has become less of a “nice-to-have” and more of a basic verification step.
A teacher wants to know if a student’s “original” illustration came from Midjourney. A marketplace wants to filter synthetic product photos. A newsroom wants a quick sanity check before publishing an image that might be manipulated.
In practice, most people aren’t asking for perfect certainty. They’re asking for something more realistic: a tool that gives a useful signal without wasting time or creating false confidence.
This comparison of Hive Moderation vs. ImageDetector.com focuses on AI image detection — not text, not deepfake voice, not moderation for everything under the sun.
What is ImageDetector?
ImageDetector.com is a web-based AI image detector built around speed and accessibility.
The workflow is simple: upload an image (or paste an image link), and it returns a likelihood result in seconds. It supports common formats like JPG, PNG, and WEBP and markets itself as free with no sign-up required.

On paper, it covers the mainstream generator landscape. The site explicitly names generators like Midjourney, GPT, Nano Banana, plus others, and frames the tool as a way to answer the everyday question: “Is this image AI?”
One detail worth noting: ImageDetector claims it analyzes the image itself rather than relying on metadata or watermarks. That’s generally the right approach, since metadata gets stripped constantly once images pass through chat apps, social platforms, and screenshots.
What is Hive Moderation?
Hive is a very different kind of product.
Hive’s “AI-Generated & Deepfake Content Detection” offering is positioned as an enterprise-grade system: APIs that scan images (and other media types) and return confidence scores. It also emphasizes that it can identify the likely generative engine used.

This isn’t just a website tool. Hive is built to plug into workflows at scale — content moderation pipelines, marketplaces, social platforms, fraud prevention systems, and any environment where image verification needs to be automated.
Hive also markets frequent model updates to cover new major generative engines as they gain popularity. In theory, that matters, because image generators evolve quickly — and detection models can lag behind if they aren’t maintained aggressively.
Let's Talk Accuracy
This is where AI image detection gets uncomfortable.
Most detectors work well on obvious synthetic images. The real challenge is the messy middle:
- AI-generated images that have been edited, cropped, or screenshotted
- Human photos that were heavily filtered or upscaled
- Low-resolution assets that lose the patterns detectors rely on
The issue isn’t that detectors never work. It’s that they can become overconfident in edge cases — and that’s where false positives (and false negatives) start doing damage.
In that context, “accuracy” isn’t just a number. It’s consistency across real-world conditions.
Hive’s positioning suggests it has a stronger shot at sustained accuracy because it’s built as an actively maintained model suite and is used in production settings that demand updates.
ImageDetector’s positioning suggests it’s built more for accessibility and quick checks — which is often what people actually need day-to-day, even if it’s not the same as enterprise-grade reliability.
ImageDetector vs. Hive: Which Detects AI Images Better?
Test #1
Verdict: ImageDetector classifies image as AI-generated.
AI Likelihood Score: 97.5%

Verdict: Hive classifies image as AI-generated.
AI Likelihood Score: 99.9%

Test #2
Verdict: ImageDetector classifies image as AI-generated.
AI Likelihood Score: 97.5%

Verdict: Hive classifies image as AI-generated.
AI Likelihood Score: 99.9%

Test #3
Verdict: ImageDetector classifies image as AI-generated.
AI Likelihood Score: 97.5%

Verdict: Hive classifies image as AI-generated.
AI Likelihood Score: 98.9%

Test #4
Verdict: ImageDetector classifies image as AI-generated.
AI Likelihood Score: 97.4%

Verdict: Hive classifies image as AI-generated.
AI Likelihood Score: 99.9%

Test #5
Verdict: ImageDetector classifies image as AI-generated.
AI Likelihood Score: 97.4%

Verdict: Hive classifies image as AI-generated.
AI Likelihood Score: 99.9%

Average Score
Test Number | ImageDetector | Hive |
#1 | 97.5% | 99.9% |
#2 | 97.5% | 99.9% |
#3 | 97.5% | 98.9% |
#4 | 97.4% | 99.9% |
#5 | 97.4% | 99.9% |
Score | 97.46% | 99.7% |
What Now?
The test results make one thing clear: both tools are strong.
Across five runs, ImageDetector averaged 97.46%. More importantly, it was steady — the scores barely moved from test to test. That kind of consistency is usually what you want from a “quick verification” tool, because it behaves predictably.
Hive averaged 99.7%, which is objectively higher. It also stayed near-perfect across the set, with only a small dip on one run.
That said, the practical decision still isn’t only about the top-line score.
If you want something you can reach for instantly — fast, simple, and free — ImageDetector is still the more convenient default, and its results here are strong enough that the tradeoff feels reasonable. Hive is the higher-ceiling option, but for most day-to-day checks, ImageDetector gives you nearly the same confidence with much less friction.
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