Varjo XR-3

Hardware Specifications

Varjo XR-3 delivers the most immersive mixed reality experience ever constructed, featuring photorealistic visual fidelity (human-eye resolution of over 70 PPD) across the widest field of view (115 degrees) of any XR headset, including eye tracking at 200 Hz. And with depth awareness, real and virtual elements blend together naturally.

The Varjo XR-3 mixed reality eye tracking headset is compatible with the iMotions VR Module.

VR Eye Tracking Headset
Display and Resolution
Full Frame Bionic Display with human-eye resolution. Focus area (27° x 27°) at 70 PPD uOLED, 1920 x 1920 px per eye Peripheral area at over 30 PPD LCD, 2880 x 2720 px per eye Colors: 99% sRGB, 93% DCI-P3
Field of View
Horizontal 115°
Eye Tracking
200 Hz with sub-degree accuracy; 1-dot calibration for foveated rendering
Refresh Rate
90 Hz
Mixed Reality
Ultra-low latency, dual 12-megapixel video pass-through at 90 Hz
XR Depth
LiDAR + RGB fusion, 40 cm–5 m operating range
Hand Tracking
Ultraleap Gemini (v5)
Comfort and Wearability
3-point precision fit headband Replaceable, easy-to-clean polyurethane face cushions Automatic interpupillary distance adjustment 59-71mm
594 g + headband 386g
Width 200 mm, height 170 mm, length 300 mm
Two headset adapters in-box Two USB-C cables (5 m) in-box PC Connections: 2 x DisplayPort and 2 x USB-A 3.0+
Positional Tracking
SteamVR™ 2.0 (recommended) or 1.0 tracking system Varjo inside-out tracking (beta) utilizing RGB video pass-through cameras
3.5mm audio jack with microphone support
we see how the person wearing the VR headset reacts to a video of a skydiver jumping out of an airplan

Powerful software

for powerful research

To analyze the eye tracking data you’ve gathered from research in virtual environments, you’ll need software that can provide the precision and accuracy your study requires. With the iMotions VR Eye Tracking Module, you can analyze your virtual eye tracking data with metrics such as:

  • Heatmaps
  • Gaze replays
  • Areas of interest (AOI)
  • Time to first fixation
  • Automated gaze-mapping: converts gaze from dynamic environments into static scenes for simpler aggregation and analysis