Here are the other differences between these two common chips.
Overall Findings
Bespoke silicon for accelerating machine learning calculations and AI.
Does not have any real secondary uses.
Can be standalone or built into a CPU or SoC.
Used in a range of modern devices, including phones and laptops.
Primarily designed to accelerate 3D rendering tasks.
Can also accelerate AI workloads.
Can be standalone or built into other processors and SoCs.
Parallel processing capabilities make them fast at many simultaneous tasks.
Has its own dedicated video memory (VRAM).
Used in every machine with a display.
The two processors also perform different tasks.
It can also accelerate AI workloads.
An NPU, however, is exclusively used to accelerate AI workloads.
GPUs can be part of aCPUor SoC, where they share the system memory with other components.
In those cases, the GPU has its own dedicated memory, called VRAM.
NPU Pros and Cons
Great for AI and machine learning calculations.
Can be included on a CPU/SoC or standalone.
Enables the latest generative AI tasks.
Can power AI calculations while CPUs and GPUs do general tasks.
Far lower power consumption than GPUs.
Limited to AI tasks.
For many, AI workloads aren’t useful at this time.
Still not as fast as GPUs at some AI tasks.
The Snapdragon X Elite chip is one of the fastest new NPUs on a modern SoC.
It delivers around 45 Tera Operations Per Second (TOPS).
Nvidia has also claimed that its GPUs can operate at up to 1,000 TOPS.
They also use far less power than CPUs and GPUs.
GPU Pros and Cons
Can render games, design work, or handle machine-learning calculations.
Offers much greater overall performance than NPUs in most tasks.
Can be scaled up in existing systems with add-in cards.
Requires masses of power to run at full speed.
Typically requires its own chip and memory.
Can take up a lot more physical space.
GPUs are predominantly designed for 3D rendering, however, which is something that NPUs can’t do.
GPUs are the best tools for rendering games, accelerating 3D workloads like CAD work.
Final Verdict
GPUs and NPUs are two pieces of capable hardware designed with different roles in mind.
Graphics cards are amazingly capable at 3D rendering and can be used for high-speed AI calculations when necessary.
NPUs are therefore far better suited for edge deployment in consumer devices that need AI capabilities.
