Hikaku: Free browser extension flags AI images without leaving your device

What it is

A new browser extension called Hikaku has landed on GitHub. As you browse, it flags images and videos that were probably made with AI, and it tells you why. The name is Japanese: hikaku (比較) means "comparison." The developers say the idea is to weigh what an image claims to be against the evidence it actually carries. Their motto, roughly:

Seeing is believing. Check anyway.

The extension is open source under the Apache 2.0 license and runs in Firefox, Chrome and Edge. Firefox users on version 140 or later (desktop and Android) can get it from Firefox Add-ons. According to the README, it's still under review in the Chrome Web Store, and Edge is next. Until then you can install it from the GitHub releases page. The project website is hikaku.io.

Privacy is the big selling point: everything runs on your own device. There's no server, no account and no usage tracking. The only download is a one-time fetch of the model weights from Hugging Face, pinned to a fixed version ("pinned by commit"). That way the model can't quietly change underneath you.

How the check works

Hikaku works in three steps:

1. Provenance first. The extension reads metadata, the extra information stored inside an image file. That includes Content Credentials (C2PA), a kind of digital proof of origin that camera makers and AI providers embed in files. Supported formats are JPEG, PNG, WebP, MP4/MOV and AVIF/HEIC. Hikaku also parses the standard IPTC, XMP and EXIF formats. It looks for things like the trainedAlgorithmicMedia label, notes such as "Made with … AI" and generator names in the software fields. It also spots the generation parameters that tools like Automatic1111, ComfyUI, InvokeAI and NovelAI write into their images. If the file says it was made with AI, that settles it.
2. Then the pixels. Most social networks strip metadata on upload. In that case, an image classifier running right in your browser scores the picture. The detector is built on SwinV2, a widely used image recognition architecture, and runs on ONNX Runtime, software that executes AI models across platforms. If you have a GPU, Hikaku uses WebGPU (the browser's access to your graphics card) and computes in fp16 (half precision). Without a GPU, the model runs on the CPU via WebAssembly (WASM) in a more heavily compressed uint8 version. The model skips screenshots and flat graphics like chat logs, app interfaces and slides. It handles those poorly and would otherwise misflag them as AI.
3. Show the evidence. Every flag lists its signals, its sources and how confident the call is. The developers draw a clear line here: the model on its own can only say "likely AI." Calling something "AI-generated" requires proof of provenance.

What it can do today

Suspicious images get a purple border (solid, double or dashed) or a dot in the corner. Hover over one and a card pops up with something like "AI-generated, 98%." A detail panel breaks down the individual signals, and you can copy them as JSON. You can also right-click any image or video and choose "Inspect for AI generation" to check it on demand.

Videos get checked too, including streams on YouTube or TikTok. For each visible video, Hikaku grabs three frames and takes the median score, the middle of the three values. For animated GIFs and WebPs, it analyzes the first, middle and last frames.

According to the feature list, here's what's coming:

One important caveat: for now, C2PA credentials are only read. Their signatures aren't verified cryptographically, so a forged credential wouldn't be caught as a fake.

How reliable is it?

The developers are unusually upfront about the limits. They tested the extension on real Reddit content with their own benchmark, hikaku-bench. The test used "weak labels," meaning not every image's label has been checked for certain. The results:

That means roughly a third of AI images go undetected. Video detection barely works yet, because, according to the README, the image model doesn't carry over well to individual video frames. Reddit strips Content Credentials and metadata on upload, so on social media Hikaku depends entirely on the image model.

The developers list these known weak spots: analog photography (one in four photos from the r/analog subreddit got misflagged), glossy product shots, 3D renders, AI videos, and face swaps on real photos, which aren't detected at all yet. The most important warning comes first, though: no flag doesn't mean a human made the image. If you find a wrong call, you can file a detection report on GitHub using the copied JSON output.

Installation and technical details

For Chrome and Edge, download hikaku-x.y.z-chrome.zip from the latest release and unzip it. Open chrome://extensions or edge://extensions, turn on Developer mode, click "Load unpacked" and pick the folder. The first image triggers a one-time model download: about 400 MB with a GPU, about 200 MB without one. The extension's progress window shows how far along it is. For networks without open internet access, you can build the extension with npm run build -- --offline so the model ships with it. The extension uses Manifest V3, the current standard for Chrome extensions.

Our take

Hikaku combines two approaches that usually come as separate tools: reading provenance data and analyzing the image itself. Unlike many online detectors, you don't have to upload images to someone else's server. That's a real privacy win. And it's rare for tools like this to explain every flag and to separate "likely AI" from "proven AI."

The developers' own numbers show how hard the problem still is, though. A 65 percent hit rate with 6 percent false positives is fine as a first hint, but not for a firm verdict. Scroll through an image-heavy page at that error rate and you'll regularly see wrong flags. And the extension can't yet catch, or barely catches, the two things that matter most for disinformation: deepfakes of real people and AI videos. On top of that, every figure comes from the developers themselves and rests on imprecise labels. There are no independent tests yet. So Hikaku works well as an extra check for curious users, journalists and moderators, but it's no substitute for careful fact-checking.