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Deep diveAI

Multimodal AI Reshaping Human-Computer Interaction: GPT-6 vs Claude-4

In 2028, multimodal AI has entered a truly practical stage. This analysis benchmarks the three leading models across video understanding, 3D generation, and physical reasoning.

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Competition among multimodal LLMs has intensified in 2028. GPT-6, Claude-4 Ultra, and the domestic flagship "Xuantie-2" are locked in fierce competition across multiple core metrics, though real-world user experience differences often speak louder than benchmark scores.

Video Understanding: From "Seeing" to "Identifying What Matters"

In video understanding tests, all three models can fully transcribe long video content and accurately answer timestamp-level questions. But the real differentiator lies in "information distillation": GPT-6's key point extraction accuracy in academic lecture videos is approximately 12 percentage points higher than competitors; Claude-4 Ultra demonstrates stronger metaphor interpretation capabilities in film content analysis; Xuantie-2 has significantly better understanding of Chinese internet videos (especially short-form content), directly related to its higher proportion of Chinese internet data in pre-training.

3D Generation: The Blurring Boundary Between Virtual and Real

3D generation is the new battlefield for multimodal models in 2028. Given a single indoor photo, GPT-6 can generate a 3D scene model with reasonable lighting, materials, and spatial layout in 23 seconds, with approximately 71% usability. Claude-4 Ultra's 3D generation focuses more on physical simulation characteristics—its generated mechanical part 3D models have an approximately 67% direct-usability rate in engineering software. Xuantie-2 performs better on Chinese scene understanding, with significantly superior comprehension of culturally nuanced content like Chinese interior design styles and food presentation.

Physical Reasoning: The Biggest Weakness Being Fixed

Physical reasoning has always been a vulnerability for multimodal models. 2028 tests show all three flagship models have made significant progress. On qualitative thermodynamic descriptions, both GPT-6 and Claude-4 Ultra can provide accurate responses, but quantitative calculation accuracy still has approximately 15-20% error rates.

Agent Capabilities: The Real Battlefield of Deployment Speed

The next battlefield for multimodal models isn't "understanding"—it's "execution." GPT-6's Agent mode supports cross-app collaborative operations, automatically breaking down user commands and invoking calendars, email, maps, and other applications to complete complex tasks. Claude-4 Ultra maintains the lead in success rates for long-range tasks (over 20 steps). Xuantie-2's Agent capabilities are still rapidly iterating, with core advantages in deep integration with Chinese workplace scenarios (DingTalk, WeCom, WPS).

The Deep Logic of Competitive Landscape

The surface is a model capability competition, but the deeper truth is a comprehensive battle of data, computing power, and organizational efficiency. GPT-6's backing includes Microsoft's cloud ecosystem and OpenAI's first-mover advantages; Claude-4 Ultra relies on Anthropic's safety-first philosophy and sustained investment in long-context technology; Xuantie-2 benefits from China's massive mobile internet data and unique scenario-driven innovation model.

In 2028's multimodal competition, there is no winner-take-all—only scenario supremacy.

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