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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.

Specifications

SpecDigit v4MATRIX-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
Shared use cases
No shared use cases
Only on Digit v4
  • Warehouse tote handling
  • Truck unloading
  • Bulk pack to conveyor
  • Recycling sortation
Only on MATRIX-3
  • Commercial services
  • Manufacturing & Industrial Automation
  • Logistics

When to pick which

When to pick Digit v4

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.

When to pick MATRIX-3

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.

AI-generated buyer guidance based on public specs.

Ready to evaluate?

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