MLX vs llama.cpp on Apple Silicon: Which Local LLM Runtime to Actually Use
One is a portable inference engine, the other an array framework that also trains — and that single difference settles almost every practical question.
Research desk
Reproducible findings, not hot takes
Technical reporting for reverse engineering, cloud security labs, vulnerability analysis, and defensive testing.
How to Build an LLM Evaluation Harness That Catches Real Regressions
Public benchmarks only shortlist a model; your own cases decide whether to ship it. Here is the dataset, the scorers and the CI gates that catch real drift.
Prompt Caching Explained: Cutting Agent Costs Without Touching the Model
Your agent re-sends the same long prefix on every step and pays to recompute it. Here is the KV mechanism, the ordering rule it forces, and the break-even math.
Speculative Decoding and Multi-Token Prediction: How LLMs Generate Faster
Decode is memory-bound, so checking several tokens in one pass is nearly free. Here is the mechanism, the arithmetic behind it, and why quality never moves.