Model comparison
Perceptron Mk1 vs Gemini 2.5 Pro
Capability radar, value bars, and side-by-side posture.
Perceptron Mk1
Not scored
value score
Gemini 2.5 Pro
93
value score
Perceptron Mk1 ctx
—
Gemini 2.5 Pro ctx
1.0M
Capability radar
Value · context · multimodal · openness · speed posture
Value head-to-head
- Gemini 2.5 Pro93
Attribute tape
| Field | Perceptron Mk1 | Gemini 2.5 Pro |
|---|---|---|
| Developer | Perceptron AI | Google DeepMind |
| Context | — | 1.0M |
| Modalities | Text, Code, Image, Audio, Video | |
| Openness | — | Proprietary Model |
| Speed | — | — |
| Price | — | $1.25/1M in · $10/1M out |
| Value score | — | 93 |
| Summary | Perceptron Mk1 is a closed-source vision-language model built for video understanding and embodied reasoning, accepting image and video inputs up to 2 FPS and returning structured outputs such as timecodes, bounding boxes, and points. It targets physical AI workloads including robotics, quality control, and sports analytics, priced at roughly 80–90% below comparable frontier multimodal models. | Google frontier multimodal model. |