A used Tesla V100 has quietly become the cheapest way to run local LLMs at home
The Nvidia Tesla V100, a former data‑center GPU, has become a cost‑effective option for running local large language models at home. Prices for used 32 GB V100 cards range from about $400 to $500, considerably lower than the $700‑$1,050 typical for used RTX 3090s. The V100 offers comparable bandwidth with more memory, making it attractive for higher‑capacity AI workloads.
- ▪The Tesla V100 is available in 16 GB and 32 GB HBM2 configurations, featuring 5,120 CUDA cores and 640 tensor cores.
- ▪As of July 2026, 32 GB V100 cards sell for roughly $400‑$500, while used RTX 3090 cards trade between $700 and $1,050.
- ▪Both the V100 and RTX 3090 have similar memory bandwidth, but the V100 provides more VRAM, enabling larger models or higher‑resolution context windows.
- ▪The lower price per gigabyte of the V100 makes it a compelling choice for hobbyists seeking to run 30‑billion‑parameter models locally.
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| Original publisher | XDA Developers |
| Canonical URL | https://www.xda-developers.com/a-used-tesla-v100-has-quietly-become-the-cheapest-way-to-run-local-llms-at-home/ |
| Publication time | Tue, 28 Jul 2026 16:00:10 GMT |
| Retrieval time | 2026-07-28T16:00:32.341Z |
| Last seen | 2026-07-28T16:00:32.341Z |
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{ "@context": "https://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "name": "Home", "item": "https://www.xda-developers.com/" }, { "@type": "ListItem", "position":"2", "name": "GPU", "item": "https://www.xda-developers.com/gpu/" }, { "@type": "ListItem", "position":"3", "name": "A used Tesla V100 has quietly become the cheapest way to run local LLMs at home", "item": "https://www.xda-developers.com/a-used-tesla-v100-has-quietly-become-the-cheapest-way-to-run-local-llms-at-home/" } ] } A used Tesla V100 has quietly become the cheapest way to run local LLMs at home By Ty Sherback Published Jul 28, 2026, 12:00 PM EDT His love of PCs and their components was born out of trying to squeeze every ounce of performance out of the family…
Excerpt limited to ~120 words for fair-use compliance. The full article is at XDA Developers.