Agility Robotics Digit v4vsMatrix Robotics MATRIX-3
Side-by-side comparison of Agility Robotics Digit v4 and Matrix Robotics MATRIX-3: specs, price, use cases and SDKs.

Digit v4
Commercial bipedal humanoid for warehouse tote handling

MATRIX-3
A safe, autonomous, and highly generalizable physical intelligence platform.
Specifications
| Spec | Digit v4 | MATRIX-3 |
|---|---|---|
| Price (USD) | $250,000 | $0 |
| Category | humanoid | humanoid |
| Payload | 16 kg | null kg |
| Runtime | 4 h | null h |
| Speed | 1.5 m/s | null m/s |
| Weight | 65 kg | null kg |
| Degrees of Freedom | 20 | null |
| Battery | LiPo, hot-swap | — |
- Warehouse tote handling
- Truck unloading
- Bulk pack to conveyor
- Recycling sortation
- Commercial services
- Manufacturing & Industrial Automation
- Logistics
When to pick which
Choose the Agility Robotics Digit v4 for immediate deployment in brownfield logistics environments where continuous operation is critical. In high-throughput warehouse scenarios, such as moving totes from shelves to conveyors, Digit’s 16kg payload capacity and hot-swappable battery system ensure minimal downtime across multi-shift schedules. Its integration with ROS2 and the Agility Arc cloud platform makes it the superior choice for enterprise-scale fleets requiring sophisticated fleet management and real-time monitoring. If your facility requires a bipedal platform that is commercially ready to handle heavy lifting in narrow aisles today, Digit’s established hardware performance provides a lower-risk path to ROI.
Opt for the Matrix Robotics MATRIX-3 if your organization is focused on developing or testing general-purpose physical intelligence rather than executing specific, high-frequency logistics tasks. This platform is positioned for buyers in manufacturing or commercial services who prioritize software adaptability and autonomous learning over fixed hardware throughput. However, because the manufacturer has not disclosed weight, payload, or runtime details, there is limited public spec data — request a vendor briefing. It is the better option for innovation labs or pilot programs looking to explore the frontiers of highly generalizable AI where the specific mechanical constraints are secondary to the underlying intelligence architecture.
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