CPU vs GPU: What’s the Difference?
- Zo Jakab
- Oct 7, 2023
- 2 min read
Updated: Oct 8
With the rapid growth of AI, machine learning, and high-performance computing, the discussion around CPUs vs GPUs has become stronger than ever. Both are essential, but they serve very different purposes inside servers and data centers.
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CPU – Central Processing Unit: CPU vs GPU
A CPU (Central Processing Unit) is the main processor in a server. It runs operating systems, applications, and background services, managing how data moves across the system.CPUs are excellent at sequential processing — handling one or a few complex tasks at a time with high precision.
They have fewer but stronger cores, higher clock speeds, and large cache memory. These features make them ideal for workloads such as:
Running virtual machines
Managing databases
Handling user requests
Processing transactions
Main CPU manufacturers: Intel, AMD, and ARM. Each produces enterprise-grade processors used in servers, storage systems, and networking equipment.
GPU – Graphics Processing Unit: CPU vs GPU
A GPU (Graphics Processing Unit) is designed for parallel processing. Instead of focusing on one complex task, it can process thousands of smaller operations at the same time.This makes GPUs perfect for tasks that need massive computational power, such as:
Artificial intelligence and deep learning
High-performance computing (HPC)
Data analysis
Scientific simulations
Image and video rendering
Modern GPUs are built with thousands of small, efficient cores and high-bandwidth memory (VRAM). They deliver extreme performance for specialized workloads that CPUs would take much longer to complete.
Main GPU manufacturers: NVIDIA, AMD, and Intel.
CPU vs GPU – Main Differences
Feature | CPU | GPU |
Primary Function | General-purpose, sequential tasks | Parallel tasks like AI, HPC, rendering |
Cores | Few, powerful cores | Thousands of smaller cores |
Clock Speed | Higher per-core frequency | Lower per-core, but massive parallelism |
Memory Type | System memory (DDR4/DDR5) | High-speed VRAM (GDDR6, HBM2) |
Workload Type | Flexible and versatile | Specialized, high-throughput workloads |
Power Usage | Lower overall | Higher due to parallel architecture |
Typical Cost | Lower | Higher, depending on performance class |
How They Work Together: CPU vs GPU
In modern server environments, CPUs and GPUs often work side by side. The CPU manages system logic, data flow, and I/O operations, while the GPU accelerates parallel workloads.This combination allows companies to achieve faster processing, improved efficiency, and better scalability for AI, analytics, and scientific computing.
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You don’t need brand-new components to achieve great performance. Refurbished CPUs and GPUs can deliver the same results for a fraction of the price — fully tested and backed by a 5-year warranty.
Server CPUs and GPUs: Save Up To 80%
✔️ 5-Year Warranty – No Risk: Pay Only After Testing
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