Google’s Open Knowledge Format (OKF) is a Markdown+YAML skeleton for sharing knowledge between humans and AI agents. This post reuses that skeleton for a very specific job — an agent-to-agent hand-off of pre-tokenized integer arrays between three Qwen2.5-Coder models (7B, 3B, 1.5B) — and shows the 28–37% TTFT reduction plus the one full-vocabulary equivalence check that keeps the whole thing safe.
The post How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs appeared first on Towards Data Science.
