DeepFake-O-Meter
Open web platform for detecting AI-generated image, video and audio.
At a glance
- Editor scoreNot yet scored
- PricingFree plan
- Best forResearchers comparing detection algorithms
- Free planYes
- Paid fromNone
- Facts checked21 Sep 2026
Where it wins
- Analyzes uploaded image, video, and audio files
- Compares algorithms by accuracy, runtime, and development year
- Returns percentage likelihoods that content was AI generated
Where it doesn't
- Requires a free account before uploads
- Available through the web platform only
- Results depend on the selected detection algorithms
Our verdict on DeepFake-O-Meter
DeepFake-O-Meter is a free, open-source web platform from the University at Buffalo Media Forensics Lab. It analyzes uploaded images, videos, and audio with multiple deepfake-detection algorithms, making it particularly suited to researchers, journalists, social media users, and others investigating potentially synthetic media. Users can select algorithms using accuracy, runtime, and development-year metrics, then review percentage likelihoods that content was AI generated. The platform requires a free account before users can upload files.
Its strongest distinction is algorithm comparison rather than a single detection result. Users can compare outputs from algorithms developed by different research groups and choose methods based on the published accuracy, runtime, and development-year metrics. That gives researchers a practical way to examine how different approaches assess the same content. Public access to open-source detection algorithms also supports investigation and comparison across image, video, and audio workflows, instead of limiting analysis to one media format.
The product is most appropriate for exploratory analysis and research-oriented review through a browser. The free, open-source model keeps access straightforward, while the optional ability to share submissions with researchers can support algorithm training. The account requirement adds an onboarding step, and the web-only format makes it less suited to teams seeking a broader deployment model. Organizations looking for an integrated production workflow should consider whether browser-based analysis and algorithm-level comparison match their needs. DeepFake-O-Meter is a strong fit for people who want to compare detection methods across media types, but a less natural choice for buyers prioritizing operational automation or a dedicated enterprise platform.
DeepFake-O-Meter pricing
DeepFake-O-Meter fact sheet
| Free plan | Yes |
|---|---|
| Paid from | None |
| Media types | image, video, audio |
| API access | Not verified |
| Face analysis | Not verified |
| Batch analysis | Not verified |
| Real-time analysis | Not verified |
| On-premises deployment | Not verified |
| Maximum file size | Not verified |
| Deployment | Cloud |
| Platforms | Web |
| Support | |
| Built for | Solo, Small business (editorial estimate) |
| Pricing | Free plan |
| Website | zinc.cse.buffalo.edu |
| Facts checked | 21 Sep 2026 |
Alternatives to DeepFake-O-Meter
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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
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