重磅发布｜极佳视界首次提出通用世界模型L1-L5分级体系 GWM正在成为AGI的最新前沿

This article highlights the core insight that ExViewer first introduced the L1-L5 classification framework for General World Models (GWM) at the 2026 World Robot Conference, which draws clear capability boundaries and charts a clear technical direction for world model development in the AGI space.

1. GWM levels L1 to L5 are defined sequentially as Video-level, Motion-level, Geometry-level, Physics-level, and Operation-level, with increasingly strict constraints on world representation. The framework progresses from only meeting visual realism requirements to enabling long-term stable operation, and higher levels do not replace lower levels — they simply add additional layers of constraints.

2. The classification framework corresponds to three interlocking technical advancement axes: representation, intelligence, and time. To date, the framework has been validated in three real-world scenarios: embodied intelligence, autonomous driving, and content creation. The classification also redefines evaluation standards for models at different levels, preventing misjudgment of demo performance as full technical capability.

ExViewer’s release of the General World Model classification framework provides clear guidance for brand building and technical positioning in the AGI industry, while highlighting the latest industrial development trends in the space.

1. From a brand marketing perspective, releasing an original classification framework at a top-tier industry conference has established ExViewer’s positioning as a standard-setter in the space. Backed by its partnership with the Beijing Key Laboratory of General World Models, the company has strengthened its technology-focused brand influence — a path that other comparable technology brands can reference.

2. In terms of industrial trends, AGI has shifted from pure language intelligence to world intelligence that requires understanding of the physical world, making General World Models the new frontier of AGI development. Clear market demand already exists in three fields: embodied intelligence, autonomous driving, and content creation, giving brands a clear direction for new track positioning.

3. For product R&D, the classification framework outlines a clear technical path, allowing brands to select a R&D direction aligned with their own positioning to avoid resource waste from misaligned strategy.

The rise of General World Models brings clear growth opportunities for AI industry sellers, while also highlighting key risks. Key takeaways are as follows:

1. On the opportunity side, AGI has entered a new phase of development, shifting from language intelligence to world intelligence. Three core scenarios — embodied intelligence, autonomous driving, and content creation — all have clear demand for higher-capability world models, and models of every capability level have matching application scenarios. Sellers can align their own technical advantages with the most suitable track.

2. For risk mitigation, the industry has long suffered from conceptual ambiguity around world models, with many practitioners equating low-level demo performance with high-level technical capability. This misrepresentation misleads the market and risks eroding brand trust, so sellers should clarify their technical positioning based on this classification framework.

3. A key takeaway is that ExViewer built technical barriers by establishing an industry standard coordinate system, a strategy that small and medium-sized AI sellers can reference: clarify capability boundaries first, then advance step-by-step.

The development of General World Models brings new business opportunities for factories, and new insights for advancing intelligent and digital transformation. Key takeaways are as follows:

1. For product design and manufacturing requirements, as General World Models are deployed in embodied intelligence and autonomous driving, market requirements for the precision of industrial robots and autonomous driving-related components have increased significantly. Geometric consistency, physical law accuracy, and long-term operational stability are now core requirements, and factories can adjust their product design and manufacturing standards to meet these needs.

2. In terms of business opportunities, the three core deployment scenarios have driven growing demand for related hardware products, from service robots to core autonomous driving components, creating sustained incremental market space. Factories can adjust capacity布局 to align with these new market demands.

3. For transformation, factories advancing intelligent and digital upgrades can align with the deployment requirements of General World Models, develop compatible hardware products that match the capability requirements of different model levels, gradually upgrade their product portfolios, and capture new industry dividends from AGI growth.

The General World Model industry now has clear pain points and new development trends, opening up new business directions for AI-focused service providers. Key takeaways are as follows:

1. Industry trends: AGI has moved beyond the language intelligence phase to the new era of world intelligence, with General World Models becoming the latest frontier of AGI development. Technology advances along three interlocking axes: representation, intelligence, and time, with large-scale deployment demand in three fields: embodied intelligence, autonomous driving, and content creation, creating very broad overall growth space for the industry.

2. Core customer pain points: The industry has long had vague conceptual boundaries for world models, with no unified classification standard for models of different capability levels and misaligned evaluation systems. This leaves customers unable to accurately assess technical capability, and often leads to misaligned R&D directions and wasted resources.

3. Deployable solutions: ExViewer’s L1-L5 classification framework provides a unified coordinate system for models of different capabilities, alongside matching evaluation standards for each level. Service providers can leverage this framework to offer customers technical consulting, evaluation, R&D matchmaking and other related services, to match the needs of customers across different scenarios.

The development of General World Models brings new demands and development directions for AI platforms, while also clarifying risks to avoid. Key takeaways are as follows:

1. Core market demand for platforms: The General World Model industry is still in an early development stage, and requires platforms to build a collaborative ecosystem connecting R&D, industry, and capital, unify industry terminology, promote R&D and deployment of technologies at all levels, and connect industry participants with application scenarios.

2. Platform operation and investment promotion direction: Platforms can organize businesses around the five L1-L5 model levels, to onboard enterprises with different technical capabilities, covering the full track from content creation (dominated by L1) to long-term operating agents (dominated by L5). Platforms can also build dedicated investment promotion and operation segments for the three core deployment scenarios to attract enterprises with different positioning.

3. Risk mitigation: Platforms should guide enterprises to clarify their technical positioning based on the classification framework, distinguish between demo performance and actual technical capability, prevent concept hype and false advertising in the industry, maintain healthy industry development, and establish classification-aligned evaluation and access standards to screen projects that actually meet capability requirements.

This article introduces a brand new classification framework for the General World Model field, representing an important new industrial development in AGI that provides a clear research framework for related studies. Key takeaways are as follows:

1. New industrial development: AGI development has expanded beyond the language intelligence of large language models, and entered the world intelligence phase that requires understanding and predicting the physical world. General World Models (GWM) have officially become the latest frontier of AGI development, with a large number of industry deployment attempts already underway. Following rapid conceptual expansion, the industry urgently needs unified standards to resolve existing confusion.

2. New theoretical contribution: Drawing on its own technical accumulation and deployment practice, ExViewer proposes the L1-L5 five-level capability classification framework, defining clear capability definitions, core problems and testing standards for each level. The framework also clarifies that the classification does not represent sequential replacement of generations, but corresponds to three interlocking technical advancement axes of representation, intelligence, and time, with higher levels adding constraints on top of lower levels.

3. Research implications: This classification framework not only clarifies the technical development path, but also reshapes existing R&D and evaluation methods, providing a unified coordinate system for industrial research. Future research can focus on technical breakthroughs at different levels, cross-level technical integration, and deployment optimization across different scenarios to drive technological progress in General World Models.