QUANTA X2
QUANTA X2
Next-Gen Humanoid Enbodied AI
Redefines the New Paradigm of Robotics
Great Wall
Embodied Intelligence Model Series
WALL-A Model
Embodied Intelligence Model: Wall-A
An unified foundation model
as a cross-domain, multi-modal intelligent embodied platform
Our WALL-A model integrates perception, reasoning, and manipulation
through a unified framework of generalized understanding and manipulation.
Having broken through from the rules and limitation in robotics programming,
we realized a total automation with high precision.
End-to-End Structure
Perception-Action
Integration
Billion-scale Parameters
10+ Billion Parameters
Parameter Scale
Generalization of Tasks and Scenarios
All-purpose
Execution Capacity
QUANTA X2
Next-Gen Humanoid Enbodied AI
Optimal Body
172cm
Height
0-2m
Work Range
Arm with Force Control
756mm
Arm's Reach
6kg
End Payload
High Performance Chassis
54cm
Width
4cm
Obstacle Clearance
15° Climbing
15° Climbing
Quanta X2
Specifications
Degree of Freedom
62
Height
172 cm
Weight
95 kg
Arm Specification
Arm's Reach
765 mm
End Payload of an Arm
6 kg
Hands
20 DOF
End Precision
±0.03 mm
TCP Speed
1.8 m/s
Body Specifications
Work Height
0–2 m
Processor Specification
Model
Self-developed Wall-A Large Operating Model
Sensors
Various Sensor Solutions including Laser Radar, IMU, and Ultrasound etc.
End-to-End Embodied Generalization
End-to-End Structure
Perception - Decision- Action
EFM-powered MCoT
High generalization and adaptability
Perception - Decision- Action
EFM-powered MCoT
High generalization and adaptability
Integrated Software & Hardware
7 DoF Arms + 15 DoF Hands
Whole body control
Multi-sensor with real-time sensing capability
Modular System with Integrated Software and Hardware
Whole body control
Multi-sensor with real-time sensing capability
Modular System with Integrated Software and Hardware
Closed-Loop Scenario-Driven Design
Ultra-thin Base
Humanoid Model
HRI (Human-Robot Interaction)
Quick Change End Effector
Humanoid Model
HRI (Human-Robot Interaction)
Quick Change End Effector
