NVIDIA H100
NVIDIA's high-performance GPU that became the standard accelerator for training and running frontier AI models, offering 3x the AI performance of its A100 predecessor.
The H100, launched in 2023 based on the Hopper architecture, features 80GB of HBM3 memory and the Transformer Engine for accelerated LLM training. Priced at $25,000-40,000, it generates approximately 3x the AI training performance of the A100. Over 3.5 million H100s shipped in 2024. The chip powered the training of GPT-4, Claude 3, Gemini, and most other frontier models. Demand exceeded supply for over a year, with wait times exceeding 36 weeks. The H100 represents approximately $150 billion in cumulative market value and is the most commercially successful AI chip ever produced.
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Related Terms
AI Compute
The computational resources — primarily GPU and TPU processing power — required to train and run AI models, typically measured in FLOP (floating-point operations) or GPU-hours.
Capex (Capital Expenditure)
Long-term investment spending by companies on physical assets like data centers, GPU clusters, and networking infrastructure — the backbone of AI deployment at scale.
Data Center
A facility housing computer systems and infrastructure used to process, store, and distribute data — increasingly built specifically for AI training and inference workloads.
Fine-Tuning
The process of further training a pre-trained AI model on a specific, smaller dataset to specialize it for a particular task or domain, requiring far less compute than training from scratch.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks — examples include GPT-4, Claude, Gemini, and Llama.
Frontier Model
The most capable and advanced AI models at any given time, typically trained with the largest compute budgets and achieving state-of-the-art performance on benchmarks.
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