AI Hardware
AI hardware encompasses specialized processors and chips designed to accelerate artificial intelligence computations and model training. We benchmarked major AI chip manufacturers and their performance metrics.
Serverless GPU Benchmark
We benchmarked eight serverless GPU models on Modal cloud platform, measuring inference performance by processing 1 million tokens and training performance by finetuning Llama 3.2-1B-Instruct on FineTome-100k dataset using 1M tokens over 5 epochs.
AI Hardware Revenue Growth at NVIDIA
We compiled leading AI chip manufacturers across the factors that drive real datacenter success, including architectural efficiency, scaling economics, and performance across demanding AI workloads.
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Explore AI Hardware
Top 30 Cloud GPU Providers & Their GPUs in 2025
We benchmarked 10 most common GPUs in typical scenarios (e.g. finetuning an LLM like Llama 3.2). Based on these learnings, if you: Ranking: Sponsors have links and are highlighted at the top. After that, hyperscalers are listed by US market share. Then, providers are sorted by the number of models that they offer.
Cloud GPUs for Deep Learning: Availability& Price / Performance
If you are flexible about the GPU model, identify the most cost-effective cloud GPU based on our benchmark of 10 GPU models in image and text generation & finetuning scenarios. If you prefer a specific model (e.g. A100), identify the lowest-cost GPU cloud provider offering it.
Top 20 AI Chip Makers: NVIDIA & Its Competitors in 2025
Based on our experience running AIMultiple’s cloud GPU benchmark with 10 different GPU models in 4 different scenarios, these are the top AI hardware companies for data center workloads.
AI Chips: A Guide to Cost-efficient AI Training & Inference
In the past decade, machine learning, particularly deep neural networks, has been pivotal in the rise of commercial AI applications. Significant advancements in the computational power of modern hardware enabled the successful implementation of deep neural networks in the early 2010s.