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AIAI Hardware

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.

Explore AI Hardware Benchmarks: Inference, Training and AI Workloads

GPU Concurrency Benchmark: H100 vs H200 vs B200 vs MI300X

AI HardwareApr 15

I have spent the last 20 years focusing on system-level computational performance optimization. We benchmarked the latest NVIDIA GPUs, including the NVIDIA’s H100, H200, and B200, and AMD’s 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 512.

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AI HardwareApr 15

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

For over two decades, optimizing compute performance has been a cornerstone of my work. We benchmarked NVIDIA’s B200, H200, H100, and AMD’s MI300X to assess 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.

AI HardwareJan 22

GPU Software for AI: CUDA vs. ROCm in 2026

Raw hardware specifications tell only half the story in GPU computing. To measure real-world AI performance, we ran 52 distinct tests comparing AMD’s MI300X with NVIDIA’s H100, H200, and B200 across multi-GPU and high-concurrency scenarios.

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