Embodied AI (Humanoid Robot) Main Control SoC Research Report, 2026

Description

Embodied AI SoC Research: Chip Vendors Are Transforming from "Single SoC Vendors" to "Full-Stack Chip Platform Providers".

The advancing chip technology provides a crucial boost to the booming embodied artificial intelligence (EAI) industry. Robots for different application scenarios have differentiated chip selection requirements, avoiding problems caused by improper selection, such as excessive computing power surplus or insufficient performance. In addition, the development of the EAI industry also relies on breakthroughs in large model technology. The intelligence level of robots has been significantly improved, enabling robots to make independent judgments and perform complex tasks.

As the EAI Market Continues to Expand and Chip Performance Requirements Keeps Rising, Chip Vendors Launch Full-Stack Solutions.

The robot chip market is in a period of rapid growth. The global shipments of general-purpose EAI robots reached 13,000 units in 2025 and is expected to exceed 50,000 units in 2026. At present, major chip giants have launched SoCs for EAI, such as NVIDIA Jetson series and Qualcomm IQ10 series. Meanwhile, they provide robot development platforms, including NVIDIA Isaac open-source platform, second-generation Rockchip RKNN neural network model conversion and optimization tool, and Black Sesame SmartX multi-dimensional intelligent computing platform for the robot industry, in a bid to meet customers' needs for rapid application deployment and model development.

Currently, EAI SoCs are evolving:

Trend 1: Requirements for Chip Computing Power Become Much Higher.

NVIDIA's new Jetson T5000 adopts the Blackwell GPU architecture, delivering up to 2070 FP4 TFLOPS of AI compute, 7.5x higher than the previous-generation Jetson Orin. The RDK S100P from Horizon Robotics (D-Robotics) integrates CPU+BPU+MCU on a single chip, delivering 120 TOPS computing power. With the increasing complexity of algorithms, robots' computing power demand is gradually rising from the current 200-500 TOPS to 500-1000 TOPS. Notably, the industry no longer simply stacks computing power but shifts to "efficiency priority". Algorithm optimization makes efficiency a core indicator.

Trend 2: Chip Vendors Evolve towards Advanced Processes

Mainstream chip vendors move towards advanced processes. NVIDIA Jetson AGX Thor adopts 4nm process, Intel Core Ultra Series 3 uses Intel 18A process, Rockchip RK3588 adopts 8nm process, and MediaTek's latest Genio Pro adopts 3nm process, substantially boosting chip performance.

Trend 3: EAI Chip Vendors Are Transforming from "Single SoC Vendors" To "Full-Stack Chip Platform Providers".

In SemiDrive's case, besides EAI cerebrum SoCs, it has also launched intelligent control cerebellum SoCs and high-performance MCUs, so as to build full-stack EAI solutions, covering the complete architecture of "cerebrum - cerebellum - body- joint". Its product matrix ranges from main control cerebrum SoCs for high-level cognition and decision, and intelligent control cerebellum chips for motion coordination and real-time control, to E3-R series MCUs for LiDAR/machine vision, motion center, dexterous hands and joint modules, realizing full-chain chip coverage.

Among them, the intelligent control cerebellum D9-Max and robot joint module MCU E311x-R have come into mass production, and built in-depth cooperation with leading robot enterprises, successfully bringing automotive-grade high performance and high reliability into the robot field.

D9 Max adopts an architecture optimized for cerebellum application. Based on hardware isolation and hardware virtualization technology, it integrates one 8-core 2.0GHz Cortex-A55 CPU cluster, one 4-core 2.0GHz Cortex-A55 CPU cluster, and 3 pairs of dual-core lockstep 800MHz Cortex-R5F, as well as computing units like 8TOPS NPU and GPU. A single chip allows for deployment of three core functions of motion control system, HMI and EtherCAT master station, integrating the functions that traditional solutions require three chips to enable into a single chip.

The high-performance MCUs (E3-R series) have made substantial progress in joint control, meeting high functional safety and cybersecurity requirements and providing one-stop solutions. As the main control chip for joint modules, E311x-R features high real-time performance and highly stable computing power output capability. It adopts dual R5F cores with a main frequency up to 400MHz. In actual R&D, the dual cores separate motor control and communication processing for dedicated core allocation and enhanced performance.

In terms of EAI cerebrum SoC, SemiDrive reuses its expertise in on-device large model capabilities in the automotive sector to develop the next-generation robot cerebrum chip R1. Adopting ARM V9.2 architecture CPU and new high-performance NPU, it supports on-device deployment of embodied end-to-end models such as MLLM/VLA under low power consumption.

Trend 4: Chip Vendors Are Launching Full-stack Self-developed Toolchains.

Rockchip launched RKNN-Toolkit2, its second-generation neural network model conversion and optimization tool. Acting as a bridge connecting mainstream deep learning frameworks and Rockchip NPU (Neural Processing Unit) hardware platforms, it is designed to help developers efficiently deploy trained AI models on embedded devices. Based on Huashan A2000, Black Sesame Technologies builds the easy-to-use Shanhai AI toolchain, covering the entire process from model optimization to on-device deployment, providing developers with an efficient model development and deployment system. SemiDrive offers complete software and hardware development kits such as the D9-Max application development kit, enabling customers and independent developers to rapidly deploy applications and conduct on-device development.

Selection of Chips and Algorithms by Embodied Robot OEMs

The EAI level is essentially the result of the co-evolution of algorithms and chips. The two are interdependent and mutually driven, forming the core closed loop of robot intelligent systems.

For example, the basic computing board of AgiBot Lingxi X2 adopts two Rockchip RK3588 chips, replacing Jetson Xavier adopted by the previous-generation, offering improvements in both cost and performance. The 6TOPS NPU of RK3588 delivers excellent performance in motion control and perception fusion scenarios while reducing power consumption by 7W. The high-compute board adopts NVIDIA Jetson Orin NX, with total AI compute of 169 TOPS.

In terms of algorithms, the cerebrum of Lingxi X2 is equipped with AgiBot's self-developed large model Genie Operator-1 (GO-1). Adopting the Vision-Language-Latent-Action (ViLLA) architecture composed of VLM (multimodal large model) and mixture-of-experts (MoE), Lingxi X2 possesses superior learning, fast few-shot generalization and continuous evolution capabilities. The cerebellum of Lingxi X2 adopts the Xyber-Edge controller for robot motion coordination and decision. With a 144-core heterogeneous computing architecture, the controller dynamically allocates reasoning tasks to NPU clusters, and control commands to FPGAs, and compresses the traditional 12-layer control architecture for motion planning into a 3-layer implicit planning structure, achieving 450Hz real-time closed-loop control, greatly superior to Tesla Optimus' 280Hz closed-loop frequency.

AgiBot has made a differentiated and complementary layout by launching three product series of Yuanzheng, Lingxi and Genie, targeting industrial manufacturing, commercial services and data research scenarios, respectively, and is advancing towards mass production and commercial deployment.

Product Code: XX019

1 EAI Market and Application Scenarios

1.1 Basic Concepts and Terminology of EAI
Basic Concepts of EAI (1)
Basic Concepts of EAI (2)
Basic Concepts of EAI (3)
Terminology of EAI (1)
Terminology of EAI (2)
1.2 Market Prospect of EAI
Evolution History of EAI
Status Quo of EAI Industry
Evolution of EAI Application Scenarios (1)
Evolution of EAI Application Scenarios (2)
EAI Market Trends
China EAI Market Size
Global Humanoid Robot Shipments
1.3 Application Prospect of EAI
Summary of Application Prospects
EAI Market Structure by Application Scenario
Community & Household Scenario: Household Service (1)
Community & Household Scenario: Household Service (2)
Community & Household Scenario: Medical / Nursing Scenario (1)
Community & Household Scenario: Medical / Nursing Scenario (2)
Smart Manufacturing Scenario: Factory Production
Smart Manufacturing Scenario: Figure Humanoid Robots Realize 24/7 Operation in Factories
Smart Manufacturing Scenario: UBTECH Walker S2 Group Collaborative Operation in Smart Factories
Smart Manufacturing Scenario: Agricultural Production
Commercial Service Scenario: KEENON Robotics
Commercial Service Scenario: Meituan "Little Wasp"
High-Risk & Rescue Scenario: DEEP Robotics LYNX M20 Wheeled-Legged Robot
High-Risk & Rescue Scenario: iFreecomm "Lingmu" Emergency Rescue Quadruped Robot and Guide Dog
1.4 Competition Summary of EAI Suppliers
Top 50 Chinese EAI Suppliers (1)
Top 50 Chinese EAI Suppliers (2)
Top 10 Foreign EAI Suppliers (1)
Global Shipments of Top 10 Humanoid Robots, 2025 (Mainstream Statistical Caliber)
Revenues of Representative EAI Enterprises (1)
Revenues of Representative EAI Enterprises (2)
Technical Routes of Representative EAI Enterprises (1)
Technical Routes of Representative EAI Enterprises (2)
Technical Routes of Representative EAI Enterprises (3)

2 Software and Hardware System Architecture of EAI

2.1 Hardware Architecture of EAI
EAI: Introduction to Hardware System
EAI Hardware List
EAI Chip List
SemiDrive: Full-Stack Chip Solutions for Robots
GigaDevice: Full-Stack Chip Solutions for Robots
Infineon: Solutions for Each Functional Module of Humanoid Robots (1)
Infineon: Solutions for Each Functional Module of Humanoid Robots (2)
Infineon: Product Layout for Humanoid Robots

2.1.1 EAI Hardware System: Computing Power and Hardware Control System
EAI Hardware System: Computing Power and Hardware Control System
EAI Hardware System: Composition of the "Cerebrum" System
EAI Hardware System: "Cerebrum" System - Application of Main Control SoC
EAI Hardware System: "Cerebellum" System - Application of FPGA
EAI Hardware System: "Cerebellum" System - Application of MCU
EAI Algorithm: Cerebrum Control Technical Route - Vision-Language-Action (VLA) Model
EAI Algorithm: Cerebrum Control Technical Route - Hierarchical Planning Architecture
EAI Algorithm: Cerebrum Control Technical Route - Cross-Robot General System
EAI Algorithm: Cerebellum Control Technical Route - Model-Based Control Method
EAI Algorithm: Cerebellum Control Technical Route - Imitation Learning
EAI Algorithm: Cerebellum Control Technical Route - Deep Reinforcement Learning
EAI Algorithm: Cerebrum-Cerebellum Collaboration Mechanism - Traditional Hierarchical Collaboration Architecture
EAI Algorithm: Cerebrum-Cerebellum Collaboration Mechanism - New Brain-Inspired Three-System Architecture ("Cerebrum - Pons - Cerebellum")
2.1.2 EAI Hardware System: Mechanical System
EAI Hardware System: Mechanical System (Bionic Skeleton)
EAI Mechanical System: Joint Module
EAI Mechanical System: Joint Module - Motor and IC
EAI Mechanical System: Joint Module - Reducer
EAI Mechanical System: Joint Module - Driver and Encoder
2.1.3 EAI Hardware System: Execution System
EAI Hardware System: Execution System (Bionic Muscle)
2.1.4 EAI Hardware System: Power Supply and Thermal Management System
EAI Hardware System: Power Supply System
EAI Hardware System: Thermal Management System
2.1.5 EAI Hardware System: Perception System
EAI Hardware System: Perception System
EAI Hardware System: Perception System Framework
EAI Hardware System: Perception System - Vision Sensor Technology
EAI Hardware System: Perception System - Radar Sensor Technology
EAI Hardware System: Perception System - Inertial Measurement Unit (IMU) Technology

2.2 Software Architecture of EAI
Introduction to EAI Software Architecture
EAI Software Architecture: Hardware Abstraction Layer (HAL)
EAI Software Architecture: Driver Execution Layer
EAI Software Architecture: Real-Time Control Layer
EAI Software Architecture: Decision & Planning Layer
EAI Software Architecture: Application Layer (Non-Real-Time Layer)
2.3 Communication Architecture of EAI
Communication Protocol of EAI
Communication Protocol of EAI: Hierarchical Architecture
Communication Protocol of EAI: Working Mechanism of EtherCAT
Communication Protocol of EAI: Structure of EtherCAT
Communication Protocol of EAI: Working Mechanism of CAN
Communication Protocol of EAI: Working Mechanism of CAN FD
Communication Protocol of EAI: CAN FD Network Framework
2.4 Grading Standard for EAI
Levels of EAI
Current Technical Level of EAI (1)
Current Technical Level of EAI (2)
Current Technical Level of EAI (3)

3 EAI Cerebrum (Main Control SoC, Controller and Large Model)

3.1 EAI Main Control SoC: Summary of Robots and Grouped Chips
- 3.1.1 EAI Main Control SoC: Summary of Robots and Grouped Chips -Humanoid Robots
- Mainstream On-device Chips and Algorithms for Humanoid Robots
- Humanoid Robots: Ubtech Walker S2, AgiBot Lingxi X2
- Humanoid Robots: Unitree H2, Leju KUAVO 5
- Humanoid Robots: Booster K1, Noetix Bumi
- Humanoid Robots: EngineAI T800, ROBOTERA L7
- Humanoid Robots: Fourier Intelligence GR-3, Xpeng IRON
- Humanoid Robots: Xiaomi CyberOne, Figure AI Figure 03
- Humanoid Robots: Tesla Optimus Gen 3
- Humanoid Robots: Noetix Hobbs 3 (Xiaonuo)
- 3.1.2 EAI Main Control SoC: Summary of Robots and Grouped Chips -Quadruped Robots
- Mainstream On-device Chips and Algorithms for Quadruped Robots
- Quadruped Robots: Unitree As2, Xiaomi CyberDog
- 3.1.3 EAI Main Control SoC: Summary of Robots and Grouped Chips - Other Robots
- Mainstream On-device Chips and Algorithms for Other Types of Robots
- Dual-Arm Mobile Robot: GigaAI Maker H01
3.2 EAI Main Control SoC: Summary of Chip Vendors
Revenues of EAI Chip Vendors
EAI Chip Vendors: Product List of SemiDrive
EAI Chip Vendors: Core Products and Evolution Route of SemiDrive
EAI Chip Vendors: Product List of NVIDIA
EAI Chip Vendors: Core Products and Evolution Route of NVIDIA
EAI Chip Vendors: Product List of Qualcomm
EAI Chip Vendors: Core Products and Evolution Route of Qualcomm
EAI Chip Vendors: Product List of Intel
EAI Chip Vendors: Core Products and Evolution Route of Intel
EAI Chip Vendors: Product List of MediaTek
EAI Chip Vendors: Core Products and Evolution Route of MediaTek
EAI Chip Vendors: Product List of Rockchip
EAI Chip Vendors: Core Products and Evolution Route of Rockchip
EAI Chip Vendors: Product List of Black Sesame Technologies
EAI Chip Vendors: Core Products and Evolution Route of Black Sesame Technologies
EAI Chip Vendors: Product List of Cambricon
EAI Chip Vendors: Core Products and Evolution Route of Cambricon
3.3 Technical Evolution Route of EAI Main Control SoC
Trend 1:
Trend 2:
Trend 3:
3.4 EAI Controller: Summary of Suppliers
EAI Controller: Revenues of EAI Controller Suppliers
EAI Controller: Product List of SEER Robotics
EAI Controller: Core Products and Evolution Route of SEER Robotics
EAI Controller: IMotion
EAI Controller: Luxshare Precision
EAI Controller: SIM Technology
EAI Controller: Chengdu Ruixingxing
EAI Controller: NIIC
EAI Controller: Pegasus?
EAI Controller: Inovance Technology
EAI Controller: Huacheng Industrial Control
3.5 Summary of EAI Large Models
- 3.5.1 EAI Large Model: VLA
- Vision-Language-Action (VLA) Model
- Origin of VLA Model: RT-1 and RT-2
- Technical Deepening of VLA Model: OpenVLA
- Wide Application of VLA Model: Figure AI Helix Model
- Wide Application of VLA Model: NVIDIA GR00T N1
- Wide Application of VLA Model: ByteDance GR-3 Model
- Wide Application of VLA Model: Horizon Robotics Released Full-Stack Open-Source VLA Foundation Model HoloBrain-0
- 3.5.2 EAI Large Model: World Model
- Basic Architecture of World Model
- Key Definition and Application Development of World Model
- Summary of EAI World Models
- AgiBot and Shanghai AI Lab Jointly Proposed Embodied 4D World Model EnerVerse
- 3D-VLA: A 3D Vision-Language-Action Generative World Model
- RoboDreamer: Learning Compositional World Models for Robot Imagination
- IRASim - World Model in Robotics
- Amap: ABot General EAI System (1)
- Amap: ABot General EAI System (2)
- UnifoLM-WMA: Unitree Open-Source World Model
- 3.5.3 Lightweight Deployment of EAI Models
- Technical Requirements for Lightweight Model Deployment
- Combination of Multimodal Fusion and Lightweight Technology
- Lightweight Technology: Cross-Modal Feature Compression
- Lightweight Technology: Dynamic Modal Selection
- Lightweight Technology Implementation: HugWBC General Humanoid Robot Controller
- Lightweight Technology Implementation: HOVER Multimodal Neural Network Controller
- Lightweight Technology Implementation: AMS (Agility Meets Stability) Framework

4 Mainstream EAI Robot Integrators

4.1 UBTECH
Products and Operation
Product Strategy
Overview of Robot SoC Configurations
Overview of Robot Model Algorithms
Parameter Comparison between General Humanoid Robots (1)
Parameter Comparison between General Humanoid Robots (2)
Parameter Comparison between General Humanoid Robots (3)
Humanoid Robot Walker S2: Dedicated Agent Technology
Humanoid Robot Walker S2: EAI Large Model Thinker
Humanoid Robot Walker S2: Self-Service Battery Swap System
Humanoid Robot Walker S2: End-to-End Human-Like Stereo Vision Perception
4.2 AgiBot
Profile
Overview of Robot SoC Configurations (1)
Overview of Robot SoC Configurations (2)
Overview of Model Algorithms
Parameter Comparison between Humanoid Robots (1)
Parameter Comparison between Humanoid Robots (2)
Parameter Comparison between Humanoid Robots (3)
Humanoid Robot: Embodied Foundation Model Genie Operator-1
Humanoid Robot: Self-Developed Controller System
Humanoid Robot: Million-Level Real Robot Dataset Open-Source Project AgiBot World
Humanoid Robot: Powerflow Core Joint Module and WITA Interactive Large Model
Supply Chain (1)
Supply Chain (2)
4.3 Unitree Robotics
Profile
Overview of Robot SoC Configurations (1)
Overview of Robot SoC Configurations (2)
Overview of Model Algorithms
Parameter Comparison between Quadruped Robots (1)
Parameter Comparison between Quadruped Robots (2)
Parameter Comparison between Quadruped Robots (3)
Parameter Comparison between Quadruped Robots (4)
Parameter Comparison between General Humanoid Robots (1)
Parameter Comparison between General Humanoid Robots (2)
Parameter Comparison between General Humanoid Robots (3)
Consumer-grade Quadruped Robot As2: Bionic Embodied Large Model
Consumer-grade Quadruped Robot As2: Self-Developed 4D LiDAR L2
Supply Chain
Customer Base
4.4 Leju Robotics
Profile
Product Overview
Overview of Robot SoC Configurations
Overview of Model Algorithms
Parameter Comparison between Robot Products (1)
Parameter Comparison between Robot Products (2)
Parameter Comparison between Robot Products (3)
Full-Stack Data Collection and Model Training System
Leju Research Framework 2.0 (1)
Leju Research Framework 2.0 (2)
Partners
4.5 Booster Robotics
Profile
Overview of Robot SoC Configurations
Parameter Comparison between Robot Products (1)
Parameter Comparison between Robot Products (2)
4.6 Noetix Robotics
Profile
Overview of Robot SoC Configurations
Overview of Model Algorithms
Parameter Comparison between General Humanoid Robots (1)
Parameter Comparison between General Humanoid Robots (2)
Parameter Comparison between Bionic Humanoid Robots (1)
Parameter Comparison between Bionic Robot Products (2)
Self-Developed "Lingjiu" Motion Control Algorithm
Bionic Robot: Self-Developed Second-Generation Bionic Head Platform
Self-Developed Expression Driven Algorithm and Multimodal Interaction Large Model
4.7 EngineAI Robotics
Profile
Overview of Robot SoC Configurations of
Parameter Comparison between Robot Products (1)
Parameter Comparison between Robot Products (2)
Motion Control Algorithm Patent: Sim2Real Technology
Energy and Structural Patents
Joint Technology Patents
Supply Chain
4.8 ROBOTERA
Profile
Overview of Robot SoC Configurations
Overview of Model Algorithms
Parameter Comparison between Robot Products (1)
Parameter Comparison between Robot Products (2)
Ctrl-World World Model
VLAW Framework
Self-Developed Native End-to-End Embodied Large Model ERA-42
ROBOTERA XHAND1 Dexterous Hand
Supply Chain and Cost Composition: Self-Developed Core Components + Cooperation with Strategic Suppliers
4.9 Fourier Intelligence
Profile
Overview of Robot SoC Configurations
Parameter Comparison between General Humanoid Robots (1)
Parameter Comparison between General Humanoid Robots (2)
Parameter Comparison between General Humanoid Robots (3)
FSA 2.0 Actuator
Galileo System
4.10 GigaAI
Profile
Product Parameters
GigaBrain
GigaWorld
4.11 Xpeng IRON
Profile
IRON Robot: Commercialization Progress and Future Planning
IRON Humanoid Robot: Product Parameter Comparison (1)
IRON Humanoid Robot: Product Parameter Comparison (2)
IRON Humanoid Robot: Product Parameter Comparison (3)
IRON Humanoid Robot: Product Parameter Comparison (4)
IRON Humanoid Robot: Product Parameter Comparison (5)
IRON Robot Main Control SoC: Self-Developed Turing AI Chip
IRON Robot Main Control SoC: Detailed Parameters of Self-Developed Turing AI Chip
IRON Robot Main Control SoC: Parameter Interpretation of Self-Developed Turing AI Chip
IRON Robot AI Large Model: Application of Second-Generation VLA Physical World Large Model
IRON Robot Cloud Foundation Model: Reusable with Automobiles
IRON Robot Perception System: Hawk-Eye Vision System
IRON Robot Cost and Supply Chain Composition: Cost of the First-Generation IRON
4.12 Xiaomi
Parameters of CyberOne Robot (1)
Parameters of CyberOne Robot (2)
Parameters of CyberOne Robot (3)
Parameters of CyberDog Quadruped Robot
Robot: VLA Foundation Model Xiaomi-Robotics-0 (1)
Robot: VLA Foundation Model Xiaomi-Robotics-0 (2)
Robot: Self-Developed Software Algorithm
Robot: CyberOne Bionic Hand (1)
Robot: CyberOne Bionic Hand (2)
Robot: Self-Developed Power System
Robot: Cost and Supply Chain Composition
Robot: Commercialization Progress and Future Planning
4.13 Tesla
Parameters of Tesla Optimus (1)
Parameters of Tesla Optimus (2)
Parameters of Tesla Optimus (3)
Mainstream On-device Computing Chip for Humanoid Robots: Tesla A15
Tesla Optimus Gen 3 Motion Control: Reinforcement Learning Model Trained by Dojo Supercomputer
Tesla Optimus Gen 3: Reuse FSD V12/V13 Vision-only Neural Network Architecture (1)
Tesla Optimus Gen 3: Reuse FSD V12/V13 Vision-only Neural Network Architecture (2)
Tesla Optimus Gen 3: Reuse FSD V12/V13 Vision-only Neural Network Architecture (3)
Tesla Optimus Gen 3: Reuse FSD V12/V13 Vision-only Neural Network Architecture (4)
Tesla Optimus Gen 3: Reuse FSD V12/V13 Vision-only Neural Network Architecture (5)
Tesla Optimus Gen 3: Motion Planning Algorithm
Tesla Optimus Gen 3: Dexterous Hand (1)
Tesla Optimus Gen 3: Dexterous Hand (2)
Tesla Optimus Gen 3: Dexterous Hand (3)
Supply Chain of Tesla Optimus
4.14 Figure AI
Profile
Overview of Robot SoC Configurations and Model Algorithms
Parameter Comparison between General Humanoid Robots
Robot: Helix AI Model
Robot: BotQ Humanoid Robot Factory
Supply Chain

5 Mainstream EAI Chip Vendors

5.1 SemiDrive
Application and Planning of EAI Products
Strategy 2.0 from Driving Intelligence to General Intelligence
Detailed Parameters of EAI "Cerebrum" SoC
Detailed Parameters of EAI "Cerebellum" SoC
EAI "Cerebrum" SoC: R1
Intelligent Control Cerebellum SoC: D9-MAX
Intelligent Control Cerebellum SoC D9-MAX: Application Solution and Development Kit
Detailed Parameters of High-Performance MCU for EAI
Joint Module Solution Based on E3119
Dexterous Hand Solution Based on E3116
LiDAR Solution Based on E3118
5.2 Rockchip
Profile
Evolution and Future Development of EAI Chips
Parameters of RK3588 Series Products
Parameters of RK182X Co-processor SoC & RV1126B Image Processor
RK182X Series Co-Processor SoCs and Application Solutions
RK3588
RK3588 Series Application Solution and Future Planning
RK3588 Application Solution: Advantech?Reinforced Vision Controller
RK3588 Application Solution: High-Performance AMR Robot Core Computing Platform Solution
RK3588 Development Toolchain: RKNN-Toolkit2
5.3 D-Robotics
Evolution and Future Development of EAI Chips
Parameters of EAI SoC Products
Parameters of EAI Developer Kit Product
Sunrise 5 Intelligent Computing Chip, CPU+BPU Heterogeneous Architecture
Intelligent Computing Chip Application Ecosystem: NIU Electric Two-Wheeler Smart Mobility
Developer Kit Application Ecosystem: SENSING?Tech's GMSL2 Series Camera Module
5.4 Black Sesame Technologies
Evolution and Future Development of EAI Chips
Huashan A2000 (1)
Huashan A2000 (2)
SesameX EAI Computing Platform Module
Huashan A2000
Huashan A2000: Adopt Self-Developed Jiushao Architecture NPU Core
Huashan A2000: Efficient, Easy-to-use Shanhai AI Toolchain
SesameX: Full-Stack Robot Platform System
5.5 Cambricon
Evolution and Future Development of EAI Chips
Detailed Parameters of EAI Chips (1)
Detailed Parameters of EAI Chips (2)
Siyuan 590: Self-Developed Intelligent Processor Microarchitecture MLUarch05
AI Computing Library: Cambricon CNNL
Computer Vision Library: CNCV
Software Development Platform: Cambricon NeuWare
MLU Inference Acceleration Engine: MagicMind
5.6 NVIDIA
Profile
EAI SoC Series and Evolution
Mainstream On-device Computing Chip for Humanoid Robots: Jetson Orin
Detailed Parameters of Jetson Orin
Mainstream On-device Computing Chip for Humanoid Robots: Jetson Thor
Detailed Parameters of Jetson Thor
NVIDIA Jetson Thor: Adopt Blackwell Architecture for GPU
NVIDIA Jetson Thor: NVIDIA Metropolis for Vision AI Agents
NVIDIA Jetson Thor: NVIDIA Holoscan for Sensor Processing to Realize Real-Time Data Stream Transmission
NVIDIA Jetson Thor: JetPack 7 Provides Complete Tools and Libraries for Building AI Edge Applications
NVIDIA Jetson Thor: Collaborate with Isaac Open-Source Robot Platform
NVIDIA DreamZero World Action Model (WAM)
NVIDIA DreamZero World Action Model (WAM): Architecture
NVIDIA DreamZero World Action Model (WAM): Advantages
Open Multimodal Model: Nemotron 3 Nano Omni Model
5.7 Qualcomm
Evolution and Future Development of EAI Chips
Detailed Parameters of Dragonwing Series Chips: IQ10, IQ9
Detailed Parameters of Dragonwing Series Chips: IQ8, IQ6, QCS8550
IQ10 Series
QCS8550 Application Solution: Robrain AI Robot Solution
5.8 Intel
EAI SoC Series and Evolution
Parameter Comparison between Core Ultra Series Products
Detailed Parameters of Intel Core i7 Series
Detailed Parameters of Intel Core i5 Series
On-device Robot Computing Chip: 3rd Generation Intel Core Ultra
3rd Generation Intel Core Ultra: 18A Process
3rd Generation Intel Core Ultra GPU Architecture: Xe3
3rd Generation Intel Core Ultra Equipped with NPU 5: Optimized Specifically for AI Tasks
5.9 MediaTek
Evolution and Future Development of EAI Chips
Genio Pro, Genio 420, Genio 360
Dimensity 9400, Dimensity 9400+
Genio Pro
Genio 420
Genio 360
Support MediaTek NeuroPilot AI Software Development Kit
5.10 Li Auto
Parameters of Mach M100
Self-Developed Chip Mach M100
Self-Developed Chip Mach M100: Internal Structure
Self-Developed Chip Mach M100: CPU Structure
Self-Developed Chip Mach M100: NPU Structure
5.11 HOUMO.AI
Evolution and Future Development of Embodied Intelligence Chips
Houmo Manjie M50 Chip (1)
Houmo Manjie M50 Chip (2)
Houmo Manjie M50: Equipped with the "Tianxuan" Architecture - Self-developed Second-Generation Compute-in-Memory IPU Design
Houmo Manjie M50 Toolchain: Houmo Dadao
5.12 Huixi Intelligent Technology
Evolution and Future Development of Embodied Intelligence Chips
Huixi R1 (1)
Huixi R1 (2)
Self-developed Turing-Complete Instruction Set
Self-developed RPU Neural Network Accelerator
Innovative Functional Safety Architecture RIF