Using AI code agents to self-optimize llama.cpp
carrigmat · x · 2026-08-27
The author shared a radical development practice: using an AI coding assistant (specifically Kimi) to perform custom performance tweaks on llama.cpp tailored to specific hardware configurations.
- Status: The official llama.cpp doesn't fully leverage NVMe arrays. The author is working on upstreaming optimizations.
- Alternative Approach: Instead of waiting, users can instruct a code agent to analyze and modify the codebase directly, achieving recursive self-improvement.
- Core Logic: The AI identifies hardware characteristics and applies corresponding performance patches, enabling frontier intelligence on local machines.
Related event: $6,000 CPU-only server runs trillion-parameter open models locally(14 posts)→
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