For most companies with around 100 staff, 100 AI subscriptions cost less over three years than one DGX Station, and they deliver more features per person. A shared DGX Station starts to make financial sense when usage moves from chat seats to high-volume, API-driven work, or when data can't leave the building. At list prices on 5 Nov 2026, 100 ChatGPT Business or Claude Team Standard seats on annual billing cost US$24,000 a year, about S$91,973 over three years. A DGX Station system such as the MSI XpertStation WS300 or HP ZGX Fury G1n (both price on request at SourceIT), assumed here at S$150,000, works out to about S$162,000 over three years before staff time, and about S$222,000 with it. The two are not substitutes, though. They buy different things.
What do 100 seats cost compared with one shared system?
| Option (100 users, 3 years) | List price | 3-year total | What you get |
|---|---|---|---|
| ChatGPT Business, standard seat (annual) | US$20/user/month | US$72,000 (about S$91,973) | Frontier models in ChatGPT, admin console, SSO, no training on workspace data |
| Claude Team, Standard seat (annual) | US$20/user/month | US$72,000 (about S$91,973) | Claude apps, SSO, no training by default, up to US$500/month pooled API credits per team |
| Microsoft 365 Copilot (enterprise add-on, annual) | US$30/user/month | US$108,000 (about S$137,959) | Copilot inside Word, Excel, Outlook and Teams, grounded in Microsoft Graph data |
| Microsoft 365 Copilot Business (SMB add-on, annual) | US$21/user/month (US$18 promotional to 31 Dec 2026) | US$75,600 at US$21 (about S$96,571) | As above, for businesses up to 300 users |
| Google Workspace Business Standard (Gemini included) | S$18.80/user/month (annual) | S$67,680 | The full Workspace suite, with Gemini in Gmail, Docs, Sheets and Meet |
| One DGX Station GB300, ownership only (illustrative) | S$150,000 assumed hardware | about S$162,354 | A private inference server for open-weight models, shared by API |
| One DGX Station GB300, with 20% of an engineer (illustrative) | plus S$20,000 a year | about S$222,354 | As above, with someone to run it |
Source: list prices from OpenAI, Anthropic, Microsoft (Singapore page, US$ before GST) and Google Singapore pricing pages, as listed on 5 Nov 2026, converted at USD/SGD 1.2774 (Trading Economics, 5 Nov 2026). The DGX Station figures are illustrative. They assume S$150,000 for the system (the ballpark used in this series; public US pricing of roughly US$93,000–125,000 for most OEMs is about S$119,000–160,000 before GST), an APC Smart-UPS SRT 3000VA at S$4,165 (listed 5 Nov 2026), an average 1 kW draw around the clock at SP Group's Q4 2026 tariff of 31.16¢/kWh with GST (S$2,729.62 a year), and, in the second row, a fifth of a DevOps engineer on S$100,000 a year. Subscription prices exclude GST and change often, so check vendor pages before you budget.
How many seats would one DGX Station have to replace?
On these assumptions, a seat at US$20 a month costs about S$919.73 over three years. The ownership-only figure of S$162,354 equals roughly 177 such seats, and the figure with staff time (S$222,354) equals about 242. At Microsoft 365 Copilot's US$30, the equivalents are about 118 and 161 seats. So for a 100-person company the subscription route is usually cheaper on paper, even before you count what the seats include that a DGX Station does not.
That last point matters most. A subscription seat gives each employee a finished product: a polished chat app, web search, file uploads, integrations, mobile apps and, in Copilot's or Gemini's case, AI inside the email and document tools staff already use. A DGX Station gives you compute. Your team still has to install a serving stack such as vLLM or NVIDIA NIM, choose and update open-weight models, put a chat interface and single sign-on in front of it, and connect it to your documents. Our post on who manages an AI supercomputer covers that workload.
A subscription buys an AI product for each person. A DGX Station buys AI capacity for the whole company. Compare them on what you need, not just on price.
Is the answer quality the same?
Not yet. The models behind ChatGPT, Claude, Gemini and Copilot are closed frontier models. On Artificial Analysis's Intelligence Index (v5, charts to Oct 2026), the leading closed models score 55 to 60, while the best model on its open-weights list scores 33. Open-weight models such as gpt-oss-120b, Qwen and DeepSeek handle drafting, summarising, classification and retrieval-based Q&A well, and they run privately on hardware you own. For hard reasoning, long agentic coding sessions or the newest multimodal features, the frontier subscriptions still lead. A lower cost per token does not mean a lower cost per correct answer.
When does a shared DGX Station make more financial sense?
- When the usage is API-driven, not chat. Batch document processing, internal applications and agents that call a model thousands of times a day are billed per token, not per seat. That is where a fixed-cost server can win. See How Many Tokens Must a DGX Station Generate Before It Pays for Itself?
- When data cannot leave your premises. Some contracts, clients or regulators make sending certain data to an overseas AI service hard to justify. Running models locally keeps that data in-house, though governance is still needed. Our post Your Company Owns the Data. But Does It Control the AI? covers the control question.
- When the headcount is large. Past roughly 200 to 250 light users, the per-seat bill on the assumptions above overtakes the cost of a shared system with an engineer looking after it, provided an open-weight model is good enough for the work.
- When you already have the skills. If an in-house platform team already runs Linux servers and containers, the staffing cost is partly sunk.
Is a hybrid usually the better answer?
For many companies, yes. A common pattern is to give premium subscription seats to the staff who rely on frontier quality every day (developers, analysts, writers) and to put everyone else, plus the automated workloads, on a shared internal platform. An internal gateway such as LiteLLM can route each request either to the local model or to a commercial API, enforce budgets per team and log usage. It is also the starting point for charging departments fairly, which we cover in How Should Companies Charge for AI Usage? and Can NVIDIA DGX Station Become the Foundation of Your Company's Private AI Cloud?
Before you buy hardware, audit what you are already paying for. Many companies discover overlapping AI tools in different departments; see Your Company Has 20 Different IT Subscriptions. Who's Actually Tracking Them? And if you are weighing the risk of relying on a single provider, Are Businesses Becoming Too Dependent on ChatGPT? is a useful companion read.
Is there a smaller step than a DGX Station?
Yes. If the aim is a private assistant for a team of 10 to 20 rather than a whole company, a GB10 system such as the NVIDIA DGX Spark 4TB at S$9,300 (listed 5 Nov 2026) is a far cheaper pilot. Measured throughput is much lower: StorageReview recorded 500 output tokens per second for gpt-oss-120b at 128 concurrent requests on DGX Spark, against 9,280 on an ASUS ExpertCenter Pro ET900N G3 (DGX Station GB300). See Can One GB10 Support 20 Employees Using AI at the Same Time? for sizing.
Buying in Singapore
SourceIT lists the MSI XpertStation WS300, HP ZGX Fury G1n, ASUS ExpertCenter Pro ET900N G3, GIGABYTE W775-V10-L01 and Supermicro ARS-511GD-NB-LCC, all price on request, in our NVIDIA DGX Spark & DGX Station collection. Tell us how many users you have, which subscriptions you pay for today and which workloads are API-driven, and we will help you size a shared system against your current seat costs. For a quotation, use Request for Quotation on the product page, call (65) 6978 3502, email Sales@sourceit.com.sg or use our contact page.
Frequently asked questions
How much do 100 ChatGPT Business seats cost? At OpenAI's list price on 5 Nov 2026, US$20 per user per month on annual billing, 100 seats cost US$24,000 a year, or about S$91,973 over three years at USD/SGD 1.2774, before GST.
Can a DGX Station replace Microsoft 365 Copilot? Not directly. Copilot works inside Word, Excel, Outlook and Teams using your Microsoft 365 data. A DGX Station runs open-weight models that you connect to your own applications, so it can replace some API and chat use but not Copilot's built-in integration.
How many users does it take for a DGX Station to be cheaper than subscriptions? On this article's illustrative assumptions, about 177 seats at US$20 a month excluding staff time, or about 242 including a fifth of an engineer. The real figure depends on the hardware quotation, your staffing and whether open-weight models meet your quality bar.
Are open-weight models as good as ChatGPT or Claude? Not at the top end. On Artificial Analysis's Intelligence Index the best open-weights model scores 33 against 55 to 60 for leading closed models. For routine drafting, summarising and document Q&A, open models are often sufficient.
Can we use both? Yes, and many companies do. Keep frontier subscriptions for staff who need them, run high-volume and confidential workloads on a shared local system, and use an internal gateway to route and meter requests.
