NAVIGATION
Definition

GPU

A Graphics Processing Unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory. Because training neural networks involves massive matrix multiplication, the parallel processing power of GPUs is critical for modern AI workloads.

Frequently Asked Questions

Why are GPUs better than CPUs for AI?

CPUs have a few powerful cores optimized for sequential tasks. GPUs have thousands of smaller cores designed to perform simple operations (like matrix multiplication) simultaneously.

What is VRAM?

Video RAM (VRAM) is the fast dedicated memory on the GPU. Modern AI models require massive VRAM (e.g. 24GB to 80GB) to store parameters during training and inference.

Quick Facts

  • CategoryHardware & Infrastructure
  • Key ApplicationModel training compute, high-throughput inference hosting, and heavy image synthesis

Coverage Trend12 Weeks

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Related AI Terms

GPU Media Coverage & Intelligence

CoreWeaveJun 18, 2026

Choosing the Right NVIDIA Platform for Running Inference on CoreWeave

Explore the ideal NVIDIA GPUs for running inference on CoreWeave-optimize latency, reduce token cost, and match your model to the ideal GPU for real-time performance.

CoreWeaveJun 18, 2026

5 Misunderstandings About Enterprise AI Training Infrastructure

Enterprise AI leaders often think more GPUs equals faster time-to-market. The reality is more complex. Read on for five misconceptions about enterprise AI training that inflate TCO and slow delivery.

CoreWeaveJun 18, 2026

CoreWeave Trains DeepSeek-V3 Benchmark in Two Minutes

CoreWeave's MLPerf® Training v6.0 results set new records, demonstrating how customers can train frontier AI models faster, scale more efficiently, and get more value from every GPU deployed.

SiliconANGLEJun 18, 2026

AI ready data is the missing link keeping enterprise AI stuck in pilot mode

Enterprises have poured billions into artificial intelligence infrastructure - GPUs, cloud capacity, model tooling - yet most deployments remain mired in experimentation rather than generating measurable business value. The bottleneck is not compute. It is AI ready data. The gap between owning data

Ars TechnicaJun 17, 2026

AI coding agents taught robots how to install GPUs and cut zip ties

Nvidia's self-improvement program for robots enlists teams of AI coding agents.

WiredJun 16, 2026

Rackspace signs definitive agreement to deploy 30MW of AMD AI compute

Rackspace and AMD have completed a deal to roll out massive GPU infrastructure globally.

QumulusAI and the shift from GPU scarcity to GPU efficiency
SiliconANGLEJun 11, 2026

QumulusAI and the shift from GPU scarcity to GPU efficiency

Neocloud provider QumulusAI announced today that it has secured more than $124 million in customer subscriptions for three-year terms with Hyperbolic and another leading artificial intelligence inference platform. These agreements cover deployments totaling 1,280 Nvidia Corp. Blackwell GPUs, deliver

VentureBeatJun 11, 2026

What AI benchmarks miss about real-world performance

Presented by F5 Enterprise AI teams have spent years solving for compute, securing GPU allocations, negotiating cloud capacity, and benchmarking training throug

NVIDIA Confidential Computing to Help Expand Apple's Private Cloud Compute
NVIDIA BlogJun 9, 2026

NVIDIA Confidential Computing to Help Expand Apple's Private Cloud Compute

NVIDIA GPUs with Confidential Computing are now used for confidential inference in Apple's Private Cloud Compute (PCC), as it expands beyond Apple's data center

Accelerate LLM model loading and increase context windows with GPUDirect on Amazon FSx for Lustre and TurboQuant
AWS ML BlogJun 1, 2026

Accelerate LLM model loading and increase context windows with GPUDirect on Amazon FSx for Lustre and TurboQuant

If you're iterating on deploying large language models (LLMs) on AWS GPU instances, you've probably noticed the larger the model to be loaded into GPU High Band