Running 16B LLMs on Low-End Hardware with Custom Optimizations
Story 1, from Hacker News
A project demonstrates running large language models on devices with minimal RAM by using custom kernels, memory optimization, and flash storage streaming. Results show 16B models running on 1GB of RAM.
Key points
- 16B models run on 1GB RAM using flash storage streaming and expert paging
- Custom 1-bit kernels and NEON-optimized code enable efficient model execution
- Models are loaded in parts, with only active experts kept in RAM
- Supported devices include Xiaomi TV Box S and jailbroken iPad Air 2013
- All techniques are implemented as patches to llama.cpp
- Includes benchmarks, model files, and setup guides for multiple devices
Why it matters
This shows how to run large models on low-end hardware, which could enable edge AI applications on older devices without requiring new hardware.
Counterpoint
The techniques require jailbreaking or root access, which may not be feasible in production environments.
Sources
- I'm making LLMs work on small and old devices (Hacker News)
This summary was written by a language model and may contain errors. Read the original for the full story.