For LLM agents making categorical decisions, Flide eliminates redundant computation by executing multiple decision branches simultaneously in one pass, delivering both speed and numerical precision that existing inference engines can't match.
Flide is an inference engine that speeds up decision models used in LLM agents by efficiently handling multiple decision branches in a single forward pass. Instead of recomputing shared parts of the model multiple times, it uses a technique called ForkAttention to track different decision paths through GPU memory, achieving up to 9.5x speedup while maintaining mathematical accuracy.