How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs
Provides a low-level orchestration pattern for developers building multi-agent systems to eliminate redundant tokenization and speed up inference.
AI Summary
A technique for sharing pre-tokenized integer arrays between multiple Qwen2.5-Coder agents via shared memory reduces Time-To-First- by 28-37%.
Excerpt
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 T