A practical guide to running local LLMs on a 24GB MacBook Pro using LM Studio, Pi, and OpenCode, with concrete models, context sizes, and config tweaks illustrating hardware-bound tradeoffs and workflow implications for developers.
A Metal-only local inference engine (ds4.c) for DeepSeek V4 Flash with 1M-token context, 2-bit quantization, and disk-backed KV cache, offering OpenAI/Anthropic-compatible local APIs but with alpha-quality code and very high RAM requirements on macOS.
Open-source test runner for Agent Skills to empirically validate SKILL efficacy via with_skill vs baseline and judge scoring, producing artifacts and HTML reports.
Apfel exposes Apple’s on-device LLM on macOS 26+ as a three-front interface (CLI, OpenAI-compatible HTTP server, and interactive chat) with zero external cost, no API keys, and full local inference.
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