- Updated: March 24, 2026
- 1 min read
Hypura: Storage‑Tier‑Aware LLM Inference Scheduler for Apple Silicon
Hypura is an innovative storage‑tier‑aware LLM inference scheduler designed specifically for Apple Silicon devices. It optimizes large language model workloads by intelligently managing memory and compute resources across different storage tiers, delivering faster inference times and reduced energy consumption. The project includes detailed architecture diagrams, performance benchmarks, installation guides, and an Ollama‑compatible server API, making it easy for developers to integrate high‑performance LLM capabilities into their macOS applications.
Key features include dynamic tier selection, seamless GPU‑CPU coordination, and extensive configurability through command‑line tools. The repository also provides comprehensive FAQs, licensing information, and contribution guidelines for the open‑source community.
Read the original repository for more technical details: https://github.com/t8/hypura
Andrii Bidochko
CTO UBOS
Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.