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| ![]() eRacks Publishes a Private-AI Sizing Guide: 70B-Class Models Run On-Premise from $5,995Plain-English guidance on how much GPU memory and system RAM each model size needs, when self-hosting beats cloud APIs, and how to keep AI data entirely in-house.
By: eRacks Open Source Systems The guide answers the question eRacks hears most from AI buyers: how big a machine do I actually need? AI servers are priced largely by GPU memory (VRAM). The guide gives a model-size-to- It also lays out the cost crossover where owning beats renting. A 30-person team paying $30 per user per month for a cloud AI service spends about $10,800 a year, every year, with all prompts transiting a third party's servers. An on-premise server covers the same everyday inference and pays for itself in under a year. For teams handling protected health information, attorney-client material, government data, or unpublished research, the calculus is simpler still: the data cannot leave their control, and a private server is the only option. eRacks AI servers run entirely on open-source software, with Ubuntu Linux plus Ollama, Open WebUI, vLLM, and PyTorch pre-installed and tested, so staff reach the AI from a browser on day one, with no per-seat fees and no data leaving the building. The guide is published at https://eracks.com/ About eRacks Open Source Systems eRacks Open Source Systems is an open-source server and storage specialist founded in 1999, headquartered in Fremont, CA, building rackmount servers, NAS, and AI inference servers configured to customer requirements. Media Contact Joseph Wolff eRacks Open Source Systems joe@eracks.com https://eracks.com End
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