By Hassan Mujtaba
Publication Date: 2026-05-10 22:00:00
New GPUs are optimized substantially for AI workloads, but what if old GPUs like the 8-year-old NVIDIA V100, costing around $100, start to outperform recent offerings in LLMs?
NVIDIA V100, an 8-Year-Old GPU, Dusted The 5-Year Old RTX 3060 & 3-Year Old RX 7800 XT With Better Performance & Efficienct In AL LLMs
The NVIDIA Volta generation was the first purely dedicated data center series that wasn’t available in the standard consumer gaming segment. Volta was the first family to feature the Tensor Core architecture, which has since become the staple for its AI advancements. The tensor core architecture was designed to handle AI tasks and has evolved massively since the Volta family, but Hardware Haven decided to test an 8-year-old V100 GPU to see how it holds up in modern-day AI LLMs.
But first, let’s recap the specifications of the NVIDIA Tesla V100 GPU. The Tesla V100 was available in two distinct form factors, an SXM board and a PCIe variant. The SXM models were housed primarily in data centers using a mezzanine connector, which allowed direct power and NVLink routing.
The V100 tested is an SXM2 model, which features 5120 cores, 320 TMUs, 128 ROPs, and 640 Tensor Cores. It packed 6 MB of L2 cache, a clock speed of up to 1530 MHz, and either 16 or 32 GB of HBM2 memory across a 4096-bit wide bus interface, resulting in 898 GB/s bandwidth. The GPU had a 250W TDP, which feels minuscule vs the current 1KW+…
