Local LLMs, which execute large language models (open-weight) on local environments such as PCs and workstations, are gaining significant attention.

One primary driver is the risk of service suspension associated with cloud AI services. In 2026, an incident occurred where Anthropic models became temporarily unavailable due to the impact of U.S. government export controls. Additionally, Tomoko Akane, President of the International Criminal Court (ICC), revealed in an interview with the Sankei Shimbun that there is a risk her private Gmail account could become unusable due to U.S. sanctions. Local LLMs, which are downloaded once for use, are characterized by their resilience to such service termination risks.

From a technical perspective, the performance of open-weight models is improving rapidly. Representative examples include the emergence of DeepSeek R1 in 2025 and the evolution of the Qwen series deployed by Alibaba Cloud. In particular, Qwen3.8-27B is said to be comparable to Anthropic's Claude Opus 4.6, and Chinese models have demonstrated high performance in benchmarks. As model diversification progresses, the choice of where to host the AI execution environment has become critical from the perspectives of data protection, cost, and latency.

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