SCS(SH:601555) 智通财经网·2026-02-27 07:07Core Insights - The evaluation system for cloud-based large models is shifting from purely capability metrics to the actual completion of tasks, with a focus on code capabilities and multi-agent systems by leading overseas companies since 2026 [1] - The dual capability stack of "fast interaction + long reasoning" is expected to become a significant evolution direction for general-purpose agents in the near future [2] - The collaboration between edge models and cloud models is emphasized, with edge models handling high-frequency, lightweight tasks locally, while heavier reasoning tasks are processed in the cloud [3] Cloud Models - The expansion of capability boundaries and cost restructuring are occurring simultaneously in cloud models, with a focus on task completion [1] - Leading companies are intensively laying out code capabilities and multi-agent systems to enhance performance [2] Code Models - The reasoning demands in the era of intelligent agents are evolving along two optimization directions: long-chain complex reasoning and real-time interaction [2] - Low-latency agents like OpenAI's Codex-Spark prioritize interactive AI experiences, while agents like Claude4.6 focus on improving success rates in complex tasks through increased context length [2] Edge Models - The evolution of edge models is characterized by efficiency optimization and capability compression under a collaborative framework with cloud models [3] - Multi-modal capabilities are becoming a key competitive point for edge models, with a focus on achieving zero-latency interactions [3] Hardware Reconstruction - The industry is expected to focus on high-frequency demand scenarios in 2024, with a shift towards multi-modal creative capabilities by 2025 [4] - Key components for edge models are undergoing upgrades in memory and power consumption to enhance user experience [4] Future Outlook - Next-generation flagship SoC platforms like Qualcomm's Snapdragon 8 Elite Gen 6 are anticipated to provide enhanced hardware support for the complexity and multi-modality of edge AI functions [5]