Hibana supercharges local AI agents

🔥 What happened Researchers from TU Darmstadt and NYCU unveiled Hibana, an inference engine built specifically for unified-memory devices. On a single DGX Spark, it completes up to 3.4× more agentic tasks per hour than vLLM and similar frameworks. 💡 Why it matters Existing engines like vLLM are tuned for datacenter GPUs with separate host memory and leave local SoCs' memory hierarchy on the table. Hibana co-designs model surgery, persistent agent state, and adaptive speculation around shared memory and limited bandwidth — enabling 125B-parameter models on one device. ⚡ Our take Local agents have been a toy. If Hibana delivers, the laptop becomes a real challenger to the cloud — and the privacy debate gets a whole new twist.