Local AI vs Cloud API Cost: 12-Month 70B Model (Singapore)

Is it cheaper to run a 70B-class language model on your own hardware or to keep paying a cloud API per token? For a Singapore team the answer depends on three numbers: how many tokens you push through each day, which cloud model you are comparing against, and what the hardware costs once, including electricity. This post builds a transparent 12-month cost model around the ASUS Ascent GX10 (S$7,200 for the 1 TB unit) and compares it with two kinds of cloud pricing we verified on 18 October 2026: a hosted open-weight 70B model and a frontier proprietary model. Every assumption is in a table so you can swap in your own figures, and the AI hardware calculator will tell you whether a 70B model fits the box in the first place.

Why "local AI vs cloud cost" is not one question

Cloud APIs bill per million tokens, forever, and the price depends heavily on the model. A hosted open-weight 70B model is cheap per token; a frontier proprietary model costs several times more, and its output tokens cost five times its input tokens. Local hardware is the opposite shape: a one-off purchase, then electricity and a throughput ceiling. So the comparison has to be stated twice. Against a hosted 70B model, local hardware has to beat a low per-token price. Against a frontier model the bar is lower, but you are also trading model quality, not just cost. We model both so you can see where the Ascent GX10 wins and where it does not.

Assumptions: the published prices we used

Cloud prices exclude any volume discount, batch tier or cached-input pricing; those can lower the cloud column. Local costs exclude staff time, a UPS and the optional second unit, which raise the local column. We return to both in the caveats.

Scenario A: a five-person team using an assistant during office hours

Assume 1 million input tokens and 100,000 output tokens a day, which is a team summarising documents, drafting and asking questions for eight hours. Over 22 working days that is 22M input and 2.2M output tokens a month.

At this volume the GX10 does not pay for itself inside 12 months against any of the three cloud options. If the only driver is cost, a light office-hours workload belongs on an API. The reasons to buy hardware here are data residency, offline operation or a lab for developers, not the bill.

Scenario B: always-on agents working around the clock

Now assume agents that run continuously: 6 million input tokens and 600,000 output tokens a day, every day, or 180M input and 18M output tokens a month. The output side averages roughly seven tokens per second across 24 hours, a rate chosen to stay inside what a single unit serving a 4-bit 70B model can plausibly sustain. Electricity is now 24/7 at the full 240 W, or 172.8 kWh a month.

Break-even is the hardware price divided by the monthly cloud saving after electricity: S$7,200 divided by (S$691 minus S$54) is 11.3 months against the mid-tier frontier model, and S$7,200 divided by (S$1,382 minus S$54) is 5.4 months against the top-tier model. Against a hosted 70B model at US$1.04 the saving is only about S$210 a month, so one unit takes nearly three years to pay back. The pattern is consistent: local hardware wins quickly when it displaces frontier per-token pricing, and slowly or never when it displaces a cheap hosted open-weight model at modest volume.

What the numbers do not capture

Quality is not equal. Scenario B compares a 70B open-weight model against proprietary frontier models. For many internal tasks a well-chosen 70B model is adequate; for the hardest reasoning tasks the cloud column buys more capability per token.

Throughput is a ceiling, not a bill. A cloud API absorbs any burst instantly. One GX10 serves what its 128 GB of unified memory and 273 GB/s bandwidth allow; for ten times Scenario B's output you need more units (two direct, four via a switch) or a bigger class of machine such as the ExpertCenter Pro ET900N G3.

Staffing. Someone has to keep DGX OS updated and run the model server; see DGX OS updates for GX10 owners. SourceIT commissions units already updated and serving, but ongoing care is a cost the table leaves out.

Cloud discounts. Batch tiers, prompt caching and committed-use contracts can cut the cloud column. Re-run the arithmetic with the rate you are offered.

Residual value. After 12 months the GX10 still exists; the cloud spend does not. Over 24 or 36 months the local column flattens while every cloud line keeps climbing.

The hybrid pattern most teams end up with

The cost model points to a split rather than a winner. Run the steady, high-volume, data-sensitive work locally: retrieval over internal documents, classification, summarisation, coding assistants, agents that poll systems all night. Send the occasional hard problem to a frontier API, where the per-token price is affordable because the volume is small. ASUS positions the Agent Computer programme around this cloud, local or hybrid choice, and NVIDIA's Personal AI Router on the GX10 lets one endpoint route between local and remote models. The GX10 absorbs the part of the bill that grows; the API handles the part that does not.

PDPA and data residency: the cost you cannot put in a table

For personal data under Singapore's PDPA, client files, source code or anything under contractual confidentiality, a local model means the prompt never leaves the office, which removes a data-transfer review, a vendor assessment and a line in your risk register. For government and regulated buyers who cannot send data to an overseas endpoint at all, the cloud column is not an option, and the GX10 at S$7,200 is the cheapest 70B-capable machine in our range. See the DGX Spark enterprise deployment guide for the network and access-control side.

Buying an Ascent GX10 in Singapore

SourceIT is an authorised ASUS reseller and stocks the Ascent GX10 1 TB at S$7,200, the 2 TB at S$8,050 and the 4 TB at S$9,850, with official ASUS Singapore warranty. Tell us your daily token volume and intended model and we will re-run this model with your figures, size the unit or cluster, and deliver it commissioned: updated, networked and serving. Education and NVIDIA Inception pricing may apply. Use Request for Quotation on the product page, call (65) 6978 3502, or email Sales@sourceit.com.sg. GeBIZ and Vendors@Gov registered. For the wider GB10 field, see the GB10 buyer's guide.

Frequently asked questions

Is local AI cheaper than a cloud API? Only above a certain volume. In our model a GX10 pays back in about 6 to 12 months against frontier per-token pricing at 6.6M tokens a day, but takes about 34 months against a hosted 70B model at US$1.04 per million tokens, and never pays back within a year at light office-hours use.

How much electricity does an Ascent GX10 use in Singapore? At its 240 W adapter rating running 24/7, about 173 kWh a month, which is roughly S$54 at the SP Group tariff of 31.16 cents per kWh including GST for October to December 2026. Real draw is usually lower.

Which cloud prices did you use? Llama 3.3 70B serverless at US$1.04 per million tokens in and out from Together AI, and Claude Sonnet 5.5 (US$2 / US$10) and Claude Opus 5.5 (US$4 / US$20) from Anthropic's pricing page, all read on 18 October 2026.

Can one GX10 handle a whole team's agents? It handles a steady workload sized to its memory and bandwidth. For large bursts or many simultaneous users, cluster two to four units or step up to the ET900N G3, and keep an API for overflow.

Does the cost model include staff time? No. Updates, model serving and monitoring are real costs; SourceIT's commissioning covers the initial setup, and the hybrid pattern keeps the operational load small.

Why does data residency change the answer? For PDPA-regulated or confidential data, sending prompts to an overseas API may not be permitted at all, so local hardware is the only compliant option regardless of cost.