# Pangram expands AI image detection to video

> Pangram reports image and video detector results.

By BIGCHANGE.AI Editorial

Published: 2026-11-05T17:28:38.385Z
Updated: 2026-11-05T17:28:38.385Z
Canonical: https://bigchange.ai/blog/pangram-image-video-detection

![Conceptual illustration of a photograph examined with a magnifying glass.](https://bigchange.ai/api/media/file/pangram-inspection-concept.png)
AI-generated conceptual illustration by BIG CHANGE.

Pangram introduced Image 1.0 and smaller Image Flash 1.0 on November 4, adding video analysis to its image detector.

## The big change

- Image 1.0 produces a heatmap of suspected AI-generated regions.
- Flash checks video frame by frame.
- Results are signals for investigation, not proof of origin.

## From images to video

The [company says](https://www.pangram.com/blog/introducing-pangram-image-1-0) its image model accepts inputs down to 256 by 256 pixels; results below 512 carry a reduced-confidence notice. Its Chrome extension checks images; its API supports image and video. Video uploads receive frame-level analysis.

## What the tests say

Pangram reports 99.96% accuracy on an image set using 100 photographs and 1,200 synthetic counterparts from 12 generators. Its video comparison used 129 real clips and 1,400 generated clips from 14 generators; it reports a 98.7% score on DF26. The post does not detail the image accuracy calculation in its text. These are company-run evaluations.

A false positive is a real image incorrectly labeled AI-generated. In its [July preview](https://www.pangram.com/blog/introducing-pangram-image-detection), Pangram reported a 0.16% false-positive rate on 10,000 pre-2022 ReLAION images. The result concerns the earlier preview.

Independent [Community Forensics research](https://arxiv.org/html/2411.04125v2) identifies generalization to previously unseen generators as a central detection challenge. Its authors studied detector training across a large collection of generators. In consequential settings, checking original files and provenance alongside any detector result is more defensible than treating one score as a verdict.

## Sources

- [Pangram Image 1.0](https://www.pangram.com/blog/introducing-pangram-image-1-0) — Company product and evaluation.
- [Pangram research preview](https://www.pangram.com/blog/introducing-pangram-image-detection) — Earlier model evaluation.
- [Community Forensics](https://arxiv.org/html/2411.04125v2) — Independent detection research.