Benchmarking on four edge platform configurations shows hardware accelerators improve LLM inference efficiency and reveals trade-offs in power use, device size, and token throughput for constrained deployments.
Sometimes painful but certainly promising: Feasibility and trade-offs of language model inference at the edge
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Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers
Benchmarking on four edge platform configurations shows hardware accelerators improve LLM inference efficiency and reveals trade-offs in power use, device size, and token throughput for constrained deployments.