GB/Z 177.1-2026 Intelligence grading of artificial intelligence terminal—Part 1: Reference framework English, Anglais, Englisch, Inglés, えいご
This is a draft translation for reference among interesting stakeholders. The finalized translation (passing through draft translation, self-check, revision and verification) will be delivered upon being ordered.
ICS
CCS
National Standard of the People's Republic of China
GB/Z 177.1-2026
Intelligence grading of artificial intelligence terminal - Part 1: Reference framework
人工智能终端智能化分级 第1部分：参考框架
Issue date: 2026-03-31 Implementation date: 2026-10-01
Issued by the General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China
the Standardization Administration of the People's Republic of China
Contents
Foreword
Introduction
1 Scope
2 Normative References
3 Terms and Definitions
4 Abbreviations
5 Reference Framework
5.1 Overview
5.2 Hardware Devices
5.3 Operating System
5.4 Intelligent Modules
5.5 Typical Applications
5.6 Security Management
6 Terminal Classification
6.1 Overview
6.2 Computing Power
6.3 Usage Scenarios
6.4 Number of Users
6.5 AI Operation Mode
6.6 Interaction Mode
6.7 Usage Mode
6.8 Application Extension Capability
7 Capability Elements
7.1 Perception Capability
7.2 Cognition Capability
7.3 Execution Capability
7.4 Memory Capability
7.5 Learning Capability
Annex A (Informative) Terminal Classification
Bibliography
Artificial intelligence terminal intelligence classification — Part 1: Reference framework
1 Scope
This document provides a reference framework for artificial intelligence terminals and specifies the capability elements for intelligence.
This document is intended to guide the intelligence classification of various types of artificial intelligence terminals, and also provides a reference for the design, development, application, selection and evaluation of artificial intelligence terminals.
2 Normative References
The following documents are essential for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition (including any amendments) applies.
GB/T 32400 Information technology — Cloud computing — Overview and vocabulary
GB/T 41867 Information technology — Artificial intelligence — Terminology
3 Terms and Definitions
For the purposes of this document, the terms and definitions given in GB/T 32400, GB/T 41867 and the following apply.
3.1 artificial intelligence terminal
A terminal product that possesses capabilities such as proactive perception and understanding, multimodal interaction, intelligent service provision and learning evolution, and performs specific tasks.
NOTE 1: The intelligent task processing flow generally involves perception, planning, decision making, execution, learning and other stages.
NOTE 2: An artificial intelligence terminal consists of software and hardware. The software part includes artificial intelligence models, intelligent applications, operating systems, user interfaces, device cloud collaboration interfaces, etc.; the hardware part includes communication modules, processors, internal storage, peripheral input/output (I/O) devices, displays, etc.
3.2 user
A user of an artificial intelligence terminal.
NOTE: In some interaction scenarios, the user may be an intelligent system, such as an artificial intelligence terminal or an agent.
3.3 multimodal interaction
An interaction mode between a user and a terminal in which information is input and output through multiple communication methods.
NOTE: Multiple communication methods include speech, text, images, gestures, touch, eye movements, facial expressions, etc.
3.4 context awareness
The acquisition, understanding and utilisation of information about the user, environment, task and the device‘s own status.
3.5 intent understanding
The identification of a user’s underlying goal or need from user input, incorporating context awareness.
3.6 mission planning
The transformation of a user‘s goal or need into an executable task or sequence of tasks.
3.7 verification feedback
The acquisition of task execution results, verification of the degree of match with the goal, and feedback of the final execution result to the user.
3.8 knowledge learning
The optimisation of task execution or content output based on examples provided by the user, external knowledge bases, etc.
3.9 self reflection
The adjustment and optimisation of task execution or content output based on feedback or supplementary input from the user (or other intelligent agents).
3.10 model
A physical, mathematical or other logical representation of a system, entity, phenomenon, process or data.
[Source: ISO/IEC 22989:2022, 3.1.23]
3.11 device cloud collaboration
The use of cloud side computing resources and data to enhance terminal capabilities.
NOTE: In this document, this specifically refers to the use of cloud side AI computing resources to enhance terminal intelligence capabilities.
3.12 timbre
A unique acoustic perceptual characteristic used to distinguish different speakers or sounds.
4 Abbreviations
The following abbreviations apply to this document.
AI: Artificial Intelligence
APU: Accelerated Processing Unit
CIS: CMOS Image Sensor
CMOS: Complementary Metal Oxide Semiconductor
CPU: Central Processing Unit
DSP: Digital Signal Processor
eMMC: Embedded MultiMedia Card
GPGPU: General Purpose Computing on Graphics Processing Units
GPU: Graphic Processing Unit
ID: Identification
NFC: Near Field Communication
NPU: Neural Processing Unit
RAM: Random Access Memory
UFS: Universal Flash Storage
5 Reference Framework
5.1 Overview
An artificial intelligence terminal combines end side and cloud side artificial intelligence capabilities, including hardware devices, operating systems, typical applications, intelligent modules and security management, as shown in Figure 1. The artificial intelligence terminal receives user input, perceives the operating environment, understands user instructions and operational intent, and executes them. When necessary, it connects to the AI cloud and internet information via a network to achieve collaborative enhancement, and connects to external devices to achieve device control and interaction.
Depending on the type of artificial intelligence terminal (see Clause 6), relevant modules are tailored, and specific capabilities are implemented on the end side, the cloud side or through a hybrid of both.
5.2 Hardware devices
Hardware devices provide the necessary computing, storage, interaction and connectivity capabilities for the terminal, serving as the foundation of the artificial intelligence terminal. They include computing units, storage units, interaction units and communication units.
a) Computing units: Responsible for general purpose computing and AI computing. They include general purpose computing processors (e.g., CPU), units specifically designed for neural network computing (e.g., NPU), digital signal processors for audio and image processing (e.g., DSP), graphics processors for general purpose parallel computing (e.g., GPGPU), and accelerated processing units combining CPU and GPU (e.g., APU).
b) Storage units: Carry the operating system, applications, AI models and user data. They include chip based flash memory (e.g., eMMC, UFS), solid state drives and memory (e.g., RAM).
c) Interaction units: The entry point for the terminal to perceive the physical world and acquire data, including but not limited to:
Standard input devices, such as keyboards, mice, etc.;
Visual sensors, such as CMOS image sensors (CIS), infrared thermal imaging sensors, etc.;
Audio sensors, such as microphone arrays;
Motion sensors, such as accelerometers, gyroscopes, magnetometers, vibration motors, etc.;
Biosensors: such as heart rate sensors, blood oxygen saturation sensors, body temperature sensors, etc.;
Environmental sensors: such as light sensors, proximity sensors, barometers, temperature and humidity sensors, etc.
d) Communication units: Key for the terminal to connect to networks, achieve device cloud collaboration and device interconnection, including but not limited to:
Network links, such as wired networks, wireless local area networks, mobile networks (e.g., 4G, 5G), etc.;
Short range wireless communication, such as Bluetooth, SparkLink, NFC, ZigBee, etc.
5.3 Operating System
GB/Z 177.1-2026 Intelligence grading of artificial intelligence terminal—Part 1: Reference framework English, Anglais, Englisch, Inglés, えいご
This is a draft translation for reference among interesting stakeholders. The finalized translation (passing through draft translation, self-check, revision and verification) will be delivered upon being ordered.
ICS
CCS
National Standard of the People's Republic of China
GB/Z 177.1-2026
Intelligence grading of artificial intelligence terminal - Part 1: Reference framework
人工智能终端智能化分级 第1部分：参考框架
Issue date: 2026-03-31 Implementation date: 2026-10-01
Issued by the General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China
the Standardization Administration of the People's Republic of China
Contents
Foreword
Introduction
1 Scope
2 Normative References
3 Terms and Definitions
4 Abbreviations
5 Reference Framework
5.1 Overview
5.2 Hardware Devices
5.3 Operating System
5.4 Intelligent Modules
5.5 Typical Applications
5.6 Security Management
6 Terminal Classification
6.1 Overview
6.2 Computing Power
6.3 Usage Scenarios
6.4 Number of Users
6.5 AI Operation Mode
6.6 Interaction Mode
6.7 Usage Mode
6.8 Application Extension Capability
7 Capability Elements
7.1 Perception Capability
7.2 Cognition Capability
7.3 Execution Capability
7.4 Memory Capability
7.5 Learning Capability
Annex A (Informative) Terminal Classification
Bibliography
Artificial intelligence terminal intelligence classification — Part 1: Reference framework
1 Scope
This document provides a reference framework for artificial intelligence terminals and specifies the capability elements for intelligence.
This document is intended to guide the intelligence classification of various types of artificial intelligence terminals, and also provides a reference for the design, development, application, selection and evaluation of artificial intelligence terminals.
2 Normative References
The following documents are essential for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition (including any amendments) applies.
GB/T 32400 Information technology — Cloud computing — Overview and vocabulary
GB/T 41867 Information technology — Artificial intelligence — Terminology
3 Terms and Definitions
For the purposes of this document, the terms and definitions given in GB/T 32400, GB/T 41867 and the following apply.
3.1 artificial intelligence terminal
A terminal product that possesses capabilities such as proactive perception and understanding, multimodal interaction, intelligent service provision and learning evolution, and performs specific tasks.
NOTE 1: The intelligent task processing flow generally involves perception, planning, decision making, execution, learning and other stages.
NOTE 2: An artificial intelligence terminal consists of software and hardware. The software part includes artificial intelligence models, intelligent applications, operating systems, user interfaces, device cloud collaboration interfaces, etc.; the hardware part includes communication modules, processors, internal storage, peripheral input/output (I/O) devices, displays, etc.
3.2 user
A user of an artificial intelligence terminal.
NOTE: In some interaction scenarios, the user may be an intelligent system, such as an artificial intelligence terminal or an agent.
3.3 multimodal interaction
An interaction mode between a user and a terminal in which information is input and output through multiple communication methods.
NOTE: Multiple communication methods include speech, text, images, gestures, touch, eye movements, facial expressions, etc.
3.4 context awareness
The acquisition, understanding and utilisation of information about the user, environment, task and the device‘s own status.
3.5 intent understanding
The identification of a user’s underlying goal or need from user input, incorporating context awareness.
3.6 mission planning
The transformation of a user‘s goal or need into an executable task or sequence of tasks.
3.7 verification feedback
The acquisition of task execution results, verification of the degree of match with the goal, and feedback of the final execution result to the user.
3.8 knowledge learning
The optimisation of task execution or content output based on examples provided by the user, external knowledge bases, etc.
3.9 self reflection
The adjustment and optimisation of task execution or content output based on feedback or supplementary input from the user (or other intelligent agents).
3.10 model
A physical, mathematical or other logical representation of a system, entity, phenomenon, process or data.
[Source: ISO/IEC 22989:2022, 3.1.23]
3.11 device cloud collaboration
The use of cloud side computing resources and data to enhance terminal capabilities.
NOTE: In this document, this specifically refers to the use of cloud side AI computing resources to enhance terminal intelligence capabilities.
3.12 timbre
A unique acoustic perceptual characteristic used to distinguish different speakers or sounds.
4 Abbreviations
The following abbreviations apply to this document.
AI: Artificial Intelligence
APU: Accelerated Processing Unit
CIS: CMOS Image Sensor
CMOS: Complementary Metal Oxide Semiconductor
CPU: Central Processing Unit
DSP: Digital Signal Processor
eMMC: Embedded MultiMedia Card
GPGPU: General Purpose Computing on Graphics Processing Units
GPU: Graphic Processing Unit
ID: Identification
NFC: Near Field Communication
NPU: Neural Processing Unit
RAM: Random Access Memory
UFS: Universal Flash Storage
5 Reference Framework
5.1 Overview
An artificial intelligence terminal combines end side and cloud side artificial intelligence capabilities, including hardware devices, operating systems, typical applications, intelligent modules and security management, as shown in Figure 1. The artificial intelligence terminal receives user input, perceives the operating environment, understands user instructions and operational intent, and executes them. When necessary, it connects to the AI cloud and internet information via a network to achieve collaborative enhancement, and connects to external devices to achieve device control and interaction.
Depending on the type of artificial intelligence terminal (see Clause 6), relevant modules are tailored, and specific capabilities are implemented on the end side, the cloud side or through a hybrid of both.
5.2 Hardware devices
Hardware devices provide the necessary computing, storage, interaction and connectivity capabilities for the terminal, serving as the foundation of the artificial intelligence terminal. They include computing units, storage units, interaction units and communication units.
a) Computing units: Responsible for general purpose computing and AI computing. They include general purpose computing processors (e.g., CPU), units specifically designed for neural network computing (e.g., NPU), digital signal processors for audio and image processing (e.g., DSP), graphics processors for general purpose parallel computing (e.g., GPGPU), and accelerated processing units combining CPU and GPU (e.g., APU).
b) Storage units: Carry the operating system, applications, AI models and user data. They include chip based flash memory (e.g., eMMC, UFS), solid state drives and memory (e.g., RAM).
c) Interaction units: The entry point for the terminal to perceive the physical world and acquire data, including but not limited to:
Standard input devices, such as keyboards, mice, etc.;
Visual sensors, such as CMOS image sensors (CIS), infrared thermal imaging sensors, etc.;
Audio sensors, such as microphone arrays;
Motion sensors, such as accelerometers, gyroscopes, magnetometers, vibration motors, etc.;
Biosensors: such as heart rate sensors, blood oxygen saturation sensors, body temperature sensors, etc.;
Environmental sensors: such as light sensors, proximity sensors, barometers, temperature and humidity sensors, etc.
d) Communication units: Key for the terminal to connect to networks, achieve device cloud collaboration and device interconnection, including but not limited to:
Network links, such as wired networks, wireless local area networks, mobile networks (e.g., 4G, 5G), etc.;
Short range wireless communication, such as Bluetooth, SparkLink, NFC, ZigBee, etc.
5.3 Operating System
