Neural Processing Unit (NPU)
Definition
An NPU accelerates selected computations of neural networks.
A collective term for specialized processors or computing units that accelerate typical operations of neural networks. Functionality and designation vary depending on the manufacturer.
Simply explained
A special computing unit performs certain AI tasks faster than less specialized components designed for that purpose.
Why it matters in practice
Helps realistically assess model quality, limits, and technical decisions.
Example from business
A laptop runs speech or image models locally on an NPU; latency and energy consumption are measured on the target hardware.
Limits and pitfalls
- Compare NPU performance only by TOPS or ignore model support, memory, and software stack.
Origin & history
NPUs evolved from specialized AI accelerators for mobile, embedded, and server-side systems; the term does not denote a uniform cross-manufacturer architecture.
Use in mid-sized companies
- Possible application: A laptop runs speech or image models locally on an NPU; latency and energy consumption are measured on the target hardware.
Frequently asked questions
What does Neural Processor (NPU) mean?
A collective term for specialized processors or computing units that accelerate typical operations of neural networks. Functionality and designation vary depending on the manufacturer.
Which mistakes should be avoided?
Compare NPU performance only by TOPS or ignore model support, memory, and software stack.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: