# Custom Quad-GPU V100 Workstation Beats M5 Ultra

October 12, 2026 at 02:40 PM

> YouTuber Jun Yamog demonstrates a custom NVIDIA Tesla V100 cluster that outperforms modern chips in AI benchmarks using legacy hardware.

YouTuber **Jun Yamog** recently showcased a custom quad-GPU workstation utilizing four [NVIDIA Tesla V100](<https://hardwarebrief.com/entity/nvidia-tesla-q16258100>) units on an [NVLink](<https://hardwarebrief.com/entity/nvlink-q19612817>) carrier board. The setup features modified A100 heatsinks to manage 300W per chip, all connected via a PCIe x8 link with passthrough adapters.

The 2017-era Volta architecture remains potent, with each V100 offering 32GB of HBM2 memory and 900GB/s bandwidth. Benchmarks using [Qwen3.8-Flash-Next](<https://hardwarebrief.com/entity/qwen-q130234299>) show the cluster hitting 100.6 tok/s, outperforming the [M5 Ultra](<https://hardwarebrief.com/entity/apple-m5-q136505781>) and dual DGX Spark systems in prompt tasks.

This project highlights the value of legacy hardware, as a 32GB V100 currently costs $744 on eBay. The configuration proved 230 percent faster than an M5 Ultra for long prompts, proving that high-bandwidth NVLink setups still rival modern unified memory chips.


[#Nvidia](<https://hardwarebrief.com/hashtag/nvidia>) [#GPU](<https://hardwarebrief.com/hashtag/gpu>) [#Workstation](<https://hardwarebrief.com/hashtag/workstation>) [#AI](<https://hardwarebrief.com/hashtag/ai>) [#Hardware](<https://hardwarebrief.com/hashtag/hardware>)

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