Your Company Uses 1 Billion AI Tokens a Month. Should You Buy a DGX Station Instead?

At one billion tokens a month, usually not, at least not on cost alone. One billion tokens a month averages about 386 tokens per second. A DGX Station GB300 measured 45,205 tokens per second on gpt-oss-120b in StorageReview's tests, so it would sit at under 1% load. In SourceIT's illustrative model it costs about S$6,177 a month to own. At list prices, one billion tokens a month costs about S$3,690 on a Sonnet-class API (8:1 input-to-output mix) and about S$255 on a hosted open-weight model. The numbers start to favour a DGX Station at around 5 to 10 billion tokens a month, or at one billion if your work is output-heavy, needs Opus-class pricing today and an open model can do it.

What does a billion tokens a month cost on each option?

The mix of input and output tokens matters as much as the total. Retrieval and document work send long prompts and get short answers back. Drafting and agents produce much more output. The table shows both ends at four volumes. Prices are list prices from 5 Nov 2026, converted at USD/SGD 1.2774.

Sources: list API prices per million tokens as shown on OpenAI, Anthropic, Together and Fireworks pricing pages, accessed 5 Nov 2026: gpt-oss-120b US$0.15/US$0.60, Terra US$1/US$5, Sonnet 5.5 and Sol US$2/US$10, Opus 5.5 US$4/US$20. The owned cost is SourceIT's illustrative three-year model: S$150,000 hardware assumption, 1 kW average power at 31.16 cents per kWh, a fifth of an engineer at S$100,000 a year, and a UPS. Station load uses StorageReview's measured 45,205 total tokens per second for gpt-oss-120b at 8K input / 1K output, 128 concurrent requests (ASUS ET900N G3). Real-world capacity is lower than a benchmark peak.

To try your own volume and mix, set the tokens per month and the input-to-output ratio in the calculator below. Switching the comparison shows how much the choice of API moves the answer.

So when does a billion tokens justify the hardware?

Only when you pay premium rates. At one billion tokens and an 8:1 mix, the owned cost of S$6,177 a month beats only Opus-class and higher prices. At a 1:1 mix it beats Sonnet-class prices too. In both cases the saving is real only if an open-weight model gives answers that are good enough. If you are paying Opus rates because the task needs Opus-level reasoning, switching to a local model trades a cost saving for a quality risk. Claude Opus vs GPT vs Gemini vs Local LLMs looks at that trade-off.

A billion tokens sounds like a lot. Spread over a month, it is a few hundred tokens a second, which a DGX Station barely notices.

Is a DGX Station the right size for a billion tokens?

Probably bigger than you need. A month has 2.59 million seconds, so a billion tokens averages 386 tokens per second. Real demand comes in peaks during office hours, but even several times the average is a small fraction of the 45,205 tokens per second StorageReview measured. Output speed is the tighter limit. In the same test the Station produced 5,023 output tokens per second at the 8K/1K mix, which is still far above what a billion tokens a month needs.

A smaller system may be enough. StorageReview measured an NVIDIA DGX Spark at 500 output tokens per second on gpt-oss-120b at 128 concurrent requests (512 in / 512 out). A billion tokens a month at a 1:1 mix averages about 193 output tokens per second. So a GB10 system can cover that average, but busy peaks could queue. The NVIDIA DGX Spark 4TB is S$9,300 and the HP ZGX Nano G1n 4TB is S$11,499 (both listed 5 Nov 2026). GB10 vs GB300: When Is It Time to Upgrade? covers where the line falls.

What else should go into the decision?

• Growth. If usage is doubling every quarter, a billion today could be ten billion within a year. Model the volume you expect over three years, not just today's.
• Discounts you already have. Cached input is charged at a small fraction of the normal input rate (0.05 to 0.1 times on most current models), and batch jobs get 50% off at OpenAI and Anthropic. If most of your traffic is cacheable or can wait, your real API bill may be well below list price, which raises the break-even point.
• Price changes. Prices move both ways. Google's Gemini 4 Argon is due to double on 1 Dec 2026, and Gemini 3.8 Flash on 1 Jan 2027. OpenAI cut prices on its new GPT-6 tiers in October 2026. See AI Token Inflation.
• Non-cost reasons. Data that must stay on premises, regulated workloads or a need for predictable costs can justify local AI below the break-even volume. See The Sovereign AI Revolution.
• Running costs. Someone has to patch, monitor and support the system. Our post You Bought a S$150,000 AI Supercomputer. Now Who's Going to Manage It? covers the work involved.

What should a company at one billion tokens do?

Three practical steps:

1. Split your usage. Work out which workloads need a frontier model and which a good open model could handle.
2. Price the open-model share honestly. Compare against hosted open-model APIs, not only against frontier prices.
3. Pilot small. Run the open-model share on a GB10 system or a hosted open model for a quarter. If volume and quality hold up and growth continues, a DGX Station becomes a straightforward step up. How Many Tokens Must a DGX Station Generate Before It Pays for Itself? gives the break-even maths.

Buying in Singapore

SourceIT lists the DGX Station GB300 from HP (ZGX Fury G1n), MSI (XpertStation WS300), ASUS (ExpertCenter Pro ET900N G3), GIGABYTE (W775-V10-L01) and Supermicro (ARS-511GD-NB-LCC), all price on request. GB10 systems are in the NVIDIA DGX Spark & DGX Station collection. Share your monthly token mix and we can suggest the right size. 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 does one billion AI tokens a month cost? At 5 Nov 2026 list prices and an 8:1 input-to-output mix, about S$255 on hosted gpt-oss-120b, S$1,845 on GPT-6.1 Terra, S$3,690 on Claude Sonnet 5.5 or GPT-6.1 Sol, and S$7,381 on Claude Opus 5.5. At a 1:1 mix the figures roughly double.

Can one DGX Station handle a billion tokens a month? Easily. That averages about 386 tokens per second, and StorageReview measured 45,205 total tokens per second on gpt-oss-120b. The system would be lightly loaded.

Is a DGX Spark enough for a billion tokens a month? Possibly, for the average load. StorageReview measured 500 output tokens per second on gpt-oss-120b. A billion tokens a month at a 1:1 mix averages about 193 output tokens per second, but busy peaks may queue.

At what volume does a DGX Station clearly pay off? In SourceIT's illustrative model, from about 1.7 billion tokens a month against Sonnet-class list prices and about 24 billion against hosted open-model prices, assuming an open model meets your quality bar.

Does the hardware price change the answer? Yes. At S$120,000 the monthly owned cost is about S$5,343, and at S$180,000 about S$7,010. Ask us for a quotation on the configuration you need.