Browse AI chip and semiconductor resources by category.

NVIDIA designs GPU accelerators and full-stack AI platforms for data center AI training, inference, HPC, robotics, and enterprise AI workloads.

AMD builds Instinct accelerators, EPYC CPUs, ROCm software, and heterogeneous compute platforms for AI and HPC.

Groq develops LPU inference systems focused on deterministic low-latency serving for large language models.

Hopper-generation data center GPU widely used for AI training, inference, and HPC workloads.

Hopper refresh with larger HBM3e memory footprint for memory-bound inference and training tasks.

AMD data center accelerator with high HBM capacity for large model training and inference.

GPU cloud and serverless AI compute platform for training, inference endpoints, and fast experiments.

AI cloud and GPU systems provider focused on training clusters, on-demand GPUs, and AI developer infrastructure.

Specialized cloud provider for AI infrastructure, large GPU clusters, inference services, and enterprise workloads.

Marketplace for renting distributed GPU compute from independent providers with flexible price and hardware options.

Compare two popular GPU cloud options by availability, pricing model, developer workflow, and best-fit AI workloads.

A practical guide to choosing GPU cloud providers, checking availability, estimating cost, and avoiding common setup traps.

A reader-friendly walkthrough of what MLPerf measures, where it helps, and where real-world deployment can differ.

A ranking-style report on GPU cloud providers for training, inference, developer ergonomics, and procurement strategy.

A concise tracker for major AI chip export control resources, official policy references, and implementation notes.