Hi everyone, I’m Saqib, and I built PantheonGPU. I started working on it because I kept coming back to a simple question: How do I know if a GPU is actually working properly? A GPU can show up normally, have reasonable temperatures, and run workloads, but still perform below expectations or have problems that only appear under certain types of load. I wanted something that did more than just show utilization, temperature, clocks, and power. I wanted a tool that actually puts different parts of the GPU through targeted tests. PantheonGPU now has 45+ tests covering things like: • Compute and tensor performance • GPU memory bandwidth and stability • Cache behavior • PCIe performance • Thermals and power behavior • AI and LLM inference workloads • Quantized workloads • NVIDIA CUDA and AMD ROCm There is also a benchmark database so results can be compared with other systems. I’m currently working on taking PantheonGPU beyond individual GPU testing and using it to help validate larger GPU fleets. For example, finding one GPU in a server that is performing differently from the other seven. I’m also looking for GPU cloud providers and infrastructure teams interested in trying it on a small number of systems at no cost. PantheonGPU is part of the NVIDIA Inception Program. I’d really appreciate feedback, especially from people running GPUs for AI, local LLMs, homelabs, or cloud infrastructure. If you tried PantheonGPU, what would you want it to tell you about your GPU?

PANTHEON

Test your GPU. Know if it's healthy.

Test your GPU. Know if it's healthy.