Local AI worker vs a cloud chat assistant for quoting

A cloud chat assistant is the better buy for general writing and research

For many jobs, ChatGPT or Claude is the better tool, and this page does not argue otherwise. They are strong general models. They need no hardware, they start in a minute, and they write, summarise and research well. If one person occasionally asks for help wording an email, a subscription is the sensible choice. The question here is narrower: should a shared quoting desk use one, with its price list pasted in?

Quoting from your list changes four things: data, scoring, rules and sending

• The price list leaves the building. Pasting or uploading it into a cloud service is a data decision. Staffbox models run on the box, on 127.0.0.1 only; cloud is off unless you add your own key in writing.
• Nobody scores it on your quotes. A chat assistant gives an answer. It does not report how often it is right on your last 30 quotes. Staffbox does, before you pay.
• Every quote needs the same rules. A chat window can lose context unless you set up projects or memory (our view). Staffbox keeps your rules and price list in a brain, a Markdown vault you own.
• A person has to stay in the loop. Staffbox cannot send or delete. A chat assistant connected to email may be configured to send; that depends on how it is wired.

Local with the quote action vs Gemini Pro with notes only, on the same requests

We ran the same messy quoting requests through a local model and through a leading cloud model (Google's Gemini Pro), both given the same notes. The local run also had the quote action, which computes prices in code; the Gemini run had notes only. Fictional companies, a small sample. fact, our runs, fictional companies

The two runs differ in more than the model: the local one had notes plus the quote action, the cloud one had notes only, so this is not a model-against-model ranking. Without the notes, every model failed, at 1, 2 and 5 of 40. We did not test ChatGPT or Claude in this comparison, and a different cloud model could score differently. Small samples, fictional companies, and the local model here is a 27B on a GPU box. The 16 GB Mac mini with the 8B model scored 15 of 15 on a second, unseen messy set (2 Oct run, earlier version; the 6 Oct run with the current version also scored 15 of 15). Treat all of it as a hint. On a new trade it had never seen, an electrical distributor (14 Oct, Dell test box), the default Qwen3 8B setup scored 30 of 40 and 2 of 15 on messy requests, with 8 wrong prices in 55, because per-foot units, price levels and trade shorthand are not handled yet; that is why we score your own list first (the electrical result).

Cloud vendors bring certifications; a local box keeps the list in the building

OpenAI's business-data page says that, by default, it does not use inputs or outputs from ChatGPT Enterprise, ChatGPT Business, ChatGPT Edu, ChatGPT for Healthcare, ChatGPT for Teachers or its API platform for training. It says business data is encrypted at rest (AES-256) and in transit (TLS 1.2 or higher), that qualifying organisations can set how long data is kept, and that its practices align with SOC 2 Type 2 criteria and ISO/IEC 27001, 27017, 27018 and 27701 certifications. as reported, openai.com/business-data, read 13 Oct 2026 Read the page yourself before you decide; it covers business plans, not every consumer plan. We make no claim about Anthropic's terms here, because we did not read them today. The strengths are real: published certifications that Staffbox does not have, and an enterprise sales and support organisation.

Staffbox's answer is different in kind. Models run on a Mac mini in your building, nothing leaves the box, and nobody trains a model on your data. We have no SOC 2 and no cyber insurance confirmed yet.

What it costs

We do not quote prices for ChatGPT or Claude plans here, because we did not fetch a public price page today. Staffbox is priced at $595 a month at founding sites (first 100) for as long as the box is live (draft pricing) after a free 30-day pilot with no onboarding fee, or $695 a month plus $1,800 onboarding from unit 101, with the box and install included. Local work has no per-token bill (our view).

Most firms should use both, for different jobs

Yes, and we would. Our read. Use a cloud assistant for writing, research and one-off analysis. Use a scored local worker for the repeated job where the same price list answers the same kind of email every day and a person approves each draft. Staffbox can also call a cloud model on your own key if you ask in writing; it is off by default.

Sources

• OpenAI, business data privacy, security and compliance: openai.com/business-data, read 13 Oct 2026.
• Staffbox scores: evals/results on GitHub; every graded answer on the scorecard.
• ChatGPT is a trademark of OpenAI, Claude of Anthropic, Gemini of Google. Staffbox is not affiliated with them.