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AI Hardware Benchmarks: Inference, Training and AI Workloads

AI hardware are specialized processors for AI inference and model training. We analyzed major AI chip manufacturers, benchmarking the latest generation AI chips on cloud and serverless environments with different LLMs.

Serverless GPU Benchmark

Benchmarked 8 serverless GPUs on Modal for inference and Llama-3.2 finetuning.

AI Hardware Revenue Growth at NVIDIA

Mapped top AI chipmakers by efficiency, scale, and workload performance.

Explore AI Hardware Benchmarks: Inference, Training and AI Workloads

Top 30 Cloud GPU Providers & Their GPUs

AI HardwareSep 27

We benchmarked the 10 most common GPUs in typical scenarios (e.g., finetuning an LLM like Llama 3.2). Based on these learnings, if you: Ranking: Sponsors are listed with links and highlighted at the top. Next, hyperscalers are listed by their US market share. Then, providers are sorted by the number of models that they offer.

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AI HardwareSep 24

Best 10 Serverless GPU Clouds & 14 Cost-Effective GPUs

Serverless GPU can provide easy-to-scale computing services for AI workloads. However, their costs can be substantial for large-scale projects. Navigate to sections based on your needs: Serverless GPU price per throughput Serverless GPU providers offer different performance levels and pricing for AI workloads.

AI HardwareSep 23

Top 20+ AI Chip Makers: NVIDIA & Its Competitors

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 HardwareSep 12

Multi-GPU Benchmark: B200 vs H200 vs H100 vs MI300X

We benchmarked NVIDIA’s B200, H200, H100, and AMD’s MI300X to measure how well they scale for Large Language Model (LLM) inference. Using the vLLM framework with the meta-llama/Llama-3.1-8B-Instruct model, we ran tests on 1, 2, 4, and 8 GPUs. We analyzed throughput and scaling efficiency to show how each GPU architecture manages parallelized, compute-intensive workloads.

AI HardwareSep 8

GPU Concurrency Benchmark

We benchmarked the latest NVIDIA GPUs, including the NVIDIA (H100, H200, and B200) and AMD (MI300X), for concurrency scaling analysis. Using the vLLM framework with the gpt-oss-20b model, we tested how these GPUs handle concurrent requests, from 1 to 1024.

AI HardwareSep 8

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.

AI HardwareMay 30

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.

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