AgiBot Lingxi X2 (GO-1 ViLLA Model) & EngineAI PM01 (320° Waist, 2.0 m/s Human Gait) Enter Global Lab Deployment
AgiBot's 35kg, 28-DoF Lingxi X2 brings few-shot Vision-Language-Latent-Action (ViLLA) manipulation to commercial service, while EngineAI's $13,900 open-source PM01 eliminates the robotic bent-knee crouch walk.
⚡ Key Engineering & Supply-Chain Takeaways
- AgiBot Lingxi X2 ($24,900, 1.31m, 35.0kg) pairs 28 compliant degrees of freedom (including a 3-DoF waist) with the Genie Operator-1 (GO-1) ViLLA foundation model, learning new bimanual tasks from 35–50 demonstrations.
- EngineAI PM01 ($13,900, 1.38m, 40.0kg) debuts an open-source straight-knee heel-to-toe RL gait that cuts steady-state walking power by 31% at up to 2.0 m/s.
- PM01 integrates a 320-degree free-rotation waist joint and a dual-chip Intel N97 (1kHz MPC/RL) + NVIDIA Jetson Orin NX 16GB (100 TOPS VLA) compute architecture.
🔬 Technical & Supply-Chain Specification Matrix
| AgiBot Lingxi X2 Specs | 1.31m / 35.0kg / 28-to-30 DoF / GO-1 ViLLA Foundation Brain ($24,900) |
|---|---|
| EngineAI PM01 Specs | 1.38m / 40.0kg / 24 DoF w/ 320° Waist / Intel N97 + Orin NX 16GB ($13,900) |
| Locomotion Efficiency Gain | 31% Lower Walking Power via Straight-Knee Anthropomorphic RL Policy (2.0 m/s) |
Mid-Size Humanoids Split into Foundation Manipulation vs Anthropomorphic Gait
Our latest Embodied AI lab benchmark compares the $24,900 AgiBot Lingxi X2 and $13,900 EngineAI PM01 alongside Unitree's $5,900 R1:
- AgiBot Lingxi X2 (35.0kg, 28 DoF): Powered by the Genie Operator-1 (GO-1) ViLLA architecture, the X2 uses discrete latent action tokens pre-trained on the AgiBot World dataset to generalize across bimanual table manipulation and expressive human-robot interaction with under 50 demonstrations.
- EngineAI PM01 (40.0kg, 24 DoF): Replaces the traditional robotic bent-knee crouch with a straight-knee heel-to-toe RL policy that lowers knee motor winding temperatures by 14.2°C and cuts walking power by 31%, while its 320-degree rotating waist and dual Intel N97 + Jetson Orin NX brain make it a premier open-source locomotion platform.
🔗 Related AI Hardware in RECIWO Database
All 46 Devices →AgiBot Lingxi X2 Multimodal Embodied Humanoid
1.31-meter, 35kg agile humanoid robot powered by AgiBot's Genie Operator-1 (GO-1) Vision-Language-Latent-Action (ViLLA) foundation model, featuring 28 compliant degrees of freedom (including a 3-DoF waist) and expressive emotional interaction.
EngineAI PM01 Open-Source High-Dynamic Humanoid
1.38-meter, 40kg open-source bipedal research humanoid featuring a 320-degree free-rotation waist, CNC aluminum exo-skeleton, dual Intel N97 + Jetson Orin NX compute, and industry-first straight-knee natural human walking at 2.0 m/s.
Unitree R1 Ultralight Agile Humanoid Robot
25kg, 1.21-meter ultralight humanoid robot packing 26 high-torque QDD joint degrees of freedom (expandable to 40-DoF), binocular depth vision, and whole-body reinforcement learning agility.
Unitree G1 Humanoid Robot (2026 Developer Edition)
Features 23 to 43 high-torque joint degrees of freedom, 3D LiDAR + depth vision perception, and end-to-end reinforcement learning & VLA manipulation policies.
📚 Related Deep-Dive Engineering Teardowns
Browse All 88 Articles →AgiBot Lingxi X2 vs EngineAI PM01 vs Unitree R1 Benchmark: ViLLA Foundation Models, 320-Degree Waist Kinematics & Straight-Knee Gait RL
RECIWO Labs evaluated the three defining mid-size bipedal humanoids of late 2026: AgiBot's 35kg Lingxi X2 powered by the Genie Operator-1 (GO-1) ViLLA foundation model, EngineAI's 40kg open-source PM01 with its 320-degree rotating waist and 2.0 m/s straight-knee human gait, and Unitree's $5,900 25kg R1.
Unitree R1 ($5,900) vs Unitree G1 ($16,000) Developer Benchmark: 25kg Agile Locomotion, Sim-to-Real RL, and Actuator Density
RECIWO Labs put the 25kg, $5,900 Unitree R1 ultralight humanoid head-to-head against the 35kg Unitree G1 EDU and Booster T1, evaluating Quasi-Direct Drive (QDD) joint torque-to-weight ratios, Isaac Lab sim-to-real transfer, and manipulation payload limits.
Quantizing Vision-Language-Action (VLA) Models on NVIDIA Jetson Orin NX Super: FP8 vs. INT4 Control Loop Jitter
RECIWO Labs benchmarked OpenVLA-7B, Pi-0-Fast, and ACT policies on the 157 TOPS Jetson Orin NX Super, measuring action-chunk inference latency and grasp precision across FP16, FP8, and AWQ INT4.
