AI Chips Explained: GPU vs. NPU vs. TPU
Analytics Insight, Friday, July 24th, 2026
GPUs, TPUs and NPUs each serve distinct roles, optimized for workloads from training through edge inference.
The article explains how three specialized processors power contemporary machine learning.
GPUs provide flexibility for training large models with broad framework support, while Google's TPUs optimize tensor-heavy operations within its cloud ecosystem.
NPUs enable efficient on-device inference on smartphones and laptops while preserving battery life. Rather than competing, these chips work together in production systems, with GPUs or TPUs handling training and NPUs deploying models to end users.
Software maturity and framework integration often matter as much as raw specifications when choosing accelerators.