Can a Self-Hosted LLM Outperform a Cloud Model? A Hands-On Comparison of GLM, Claude, and GPT

The author, a full-stack developer at Selectel, evaluates whether self-hosted open-source LLMs can match commercial models in agentic software development. They argue that in corporate projects, the primary decision is what context can be given to the model, and only then which model to use. For closed internal repositories, they use self-hosted GLM-5.1 and GLM-5.2 via OpenCode, while external models like Claude and GPT are used for public or sanitized data. In a real integration task, GLM-5.1 with direct access to three internal repositories produced a working proof of concept in 1-2 hours with minimal engineer involvement, whereas Claude Opus 4.7 and Sonnet 4.6 required over two hours of manual context preparation and three hours of agent work due to lack of direct access. In a synthetic benchmark with identical context, GLM-5.1, Claude Opus 4.7, Claude Sonnet 4.6, and GPT-5.5 xhigh all completed a full task cycle; cross-review found Claude Opus 4.7 had the fewest (one) non-critical issues, while GLM-5.1 had four minor imperfections. The author concludes that a well-configured harness and proper context access are more critical than model choice.