Cerebras

This post introduces GLM 4.7, an open-source model that achieves up to 1500+ tokens per second on Cerebras hardware, making it 20x faster than closed-source competitors. It details GLM 4.7's capabilities in coding, tool use, and reasoning, highlighting its performance on benchmarks like 𝜏²-Bench Telecom, GPQA Diamond, and LiveCodeBench. The post provides 10 rules for optimizing GLM 4.7, focusing on prompt engineering (front-loading instructions, direct language), task management (breaking down tasks, disabling/enabling reasoning), and agentic patterns (using critics, pairing with frontier models). It also introduces the `disable_reasoning` and `clear_thinking` parameters for controlling model behavior on the Cerebras API.