Cerebras

What this post added

This post details the performance and optimization strategies for GLM 4.7, an open-source LLM, when run on Cerebras hardware. It quantifies speed improvements (20x faster than Sonnet 4.5), discusses its intelligence benchmarks, and emphasizes privacy benefits of running on Cerebras. The core technical contribution lies in the 10 rules provided for effective GLM 4.7 usage, covering prompt front-loading, direct instruction phrasing, language control, role-play leverage, task decomposition, reasoning control (enabling/disabling), the use of critic agents, pairing with frontier models, and managing memory between calls using `clear_thinking`. It also mentions specific API parameters like `disable_reasoning` and `max_completion_tokens`.