Running a mini-PC for local AI inference 24 hours a day costs between $40 and $130 per year in Australian electricity, depending on your hardware and state. A mid-range mini-PC drawing 25 watts continuously consumes 219 kilowatt-hours per year. At New South Wales rates that is roughly $70 annually. At South Australian rates, closer to $95. A NAS already running 24/7 for storage adds near-zero extra cost for AI inference. The real cost question is not the device wattage but whether you leave the hardware on all the time, and which state you are in.
In short: Most local AI hardware setups cost $40 to $130 per year in power. That is far less than a $360 annual ChatGPT Plus subscription. If your NAS is already running, AI inference adds almost nothing to the power bill. A dedicated mini-PC adds a real but manageable cost. A GPU workstation running continuously is the only scenario where power becomes a meaningful ongoing expense.
How Much Power Does Local AI Hardware Actually Use?
Power draw varies considerably by hardware class. A NAS running Ollama in the background sits at 8 to 25 watts at idle, depending on the model, how many drives are populated, and whether those drives are actively spinning or have spun down. A Synology DS925+ with four populated drives draws 15 to 22 watts at idle. The QNAP TS-473A draws similarly. A 2-bay model like the DS225+ typically runs at 5 to 10 watts at rest. The QNAP TS-464 with four drives sits around 18 to 25 watts under normal operating conditions.
Mini-PCs purpose-built for AI inference draw more power than NAS hardware, particularly under active inference load. An Intel N100-based entry mini-PC draws 10 to 15 watts at idle and 20 to 30 watts during sustained LLM token generation. A Core i5 or i7 13th-generation mini-PC draws 20 to 30 watts at idle and 40 to 60 watts while generating tokens. Core Ultra models with NPUs draw 25 to 40 watts at idle and 50 to 80 watts under sustained inference load. A desktop workstation with a discrete GPU adds dramatically more: 150 to 350 watts under GPU inference, depending on the card.
| NAS (2-bay, 2 drives) | 5 to 12W idle, 15 to 25W active |
|---|---|
| NAS (4-bay, 4 drives) | 15 to 25W idle, 30 to 45W active |
| Mini-PC (Intel N100 class) | 10 to 15W idle, 20 to 30W under inference |
| Mini-PC (Core i5/i7 13th gen) | 20 to 30W idle, 40 to 60W under inference |
| Mini-PC (Core Ultra 5/7) | 25 to 40W idle, 50 to 80W under inference |
| Desktop workstation with discrete GPU | 80 to 150W idle, 150 to 350W under GPU inference |
Australian Electricity Rates by State (2026)
Residential electricity rates in Australia vary considerably by state and retailer. South Australia has the highest residential electricity costs in the country, driven by its grid structure and the costs of high renewable energy penetration with grid-scale storage. The ACT and Queensland tend to have the lowest general usage rates, though Queensland government rebate programs can further reduce effective costs depending on the year and your eligibility. These figures are approximate 2026 general usage rates for residential customers. Your actual rate depends on your retailer, tariff structure, and whether you are on a flat rate or time-of-use plan.
Australian Electricity Rates and Annual AI Hardware Cost (2026 Approximate)
| Rate (per kWh) | 15W device 24/7 | 25W device 24/7 | 50W device 8h/day | |
|---|---|---|---|---|
| New South Wales | $0.29 to $0.37 | $38 to $48/yr | $63 to $80/yr | $42 to $54/yr |
| Victoria | $0.26 to $0.35 | $34 to $46/yr | $57 to $77/yr | $38 to $51/yr |
| Queensland | $0.26 to $0.31 | $34 to $41/yr | $57 to $68/yr | $38 to $45/yr |
| South Australia | $0.38 to $0.48 | $50 to $63/yr | $83 to $105/yr | $55 to $70/yr |
| Western Australia | $0.31 to $0.34 | $41 to $45/yr | $68 to $75/yr | $45 to $50/yr |
| Tasmania | $0.27 to $0.33 | $36 to $44/yr | $59 to $72/yr | $39 to $48/yr |
| ACT | $0.25 to $0.32 | $33 to $42/yr | $55 to $70/yr | $36 to $47/yr |
Always-On vs On-Demand: The Cost Difference
Whether you run your hardware 24 hours a day or only during active use makes a substantial difference to the annual power bill. A NAS that is already running 24/7 for file storage adds virtually zero incremental cost for running Ollama. The drives are spinning, the processor is active, the networking stack is running. Adding an occasional inference request to that baseline load costs almost nothing measurable.
A dedicated mini-PC is a different calculation. If it runs only during a typical working day (8 hours per day), a 25-watt device consumes 73 kilowatt-hours per year rather than 219 kilowatt-hours. At Queensland rates, that is approximately $19 per year rather than $57. At South Australian rates, $33 rather than $94. Most mini-PC users do not run their device around the clock, which changes the cost case considerably.
The worst case for power cost is a GPU-equipped workstation running inference continuously. A system drawing 250 watts around the clock consumes 2,190 kilowatt-hours per year. At NSW rates of $0.33 per kWh, that is approximately $720 annually. GPU rigs for local AI inference should be powered on only when actively in use unless there is a compelling operational reason to keep them on.
| NAS already running 24/7 | Near-zero incremental power cost for AI inference |
|---|---|
| Mini-PC 25W, 8h/day weekdays only | $19 to $36/yr depending on state |
| Mini-PC 25W, 24/7 | $57 to $105/yr depending on state |
| Mini-PC 50W average, 8h/day | $38 to $70/yr depending on state |
| GPU workstation 250W, 4h/day | $95 to $175/yr depending on state |
| GPU workstation 250W, 24/7 | $570 to $1,050/yr depending on state |
Local AI vs Cloud Subscription: Five-Year Cost Comparison
Cloud AI subscriptions cost between $28 and $40 AUD per month for a single user on a premium plan. That is $336 to $480 per year, or $1,680 to $2,400 over five years. API access for heavier use adds cost on top.
A mid-range mini-PC at $900 AUD, used 8 hours per day at 45 watts average draw, consumes approximately 131 kilowatt-hours per year. At NSW rates of $0.33 per kWh, that is $43 per year in power. At SA rates of $0.43 per kWh, $56 per year. Amortised hardware cost over five years is $180 per year. Total five-year cost of local AI: $1,115 to $1,180 in NSW. That compares to $1,680 to $2,400 for a single cloud subscription over the same period.
The cost advantage of local AI grows with multi-user households. Local AI serves any device on the network from one hardware investment. A household with three people, each paying for a cloud AI subscription, is spending $1,000 to $1,440 per year combined. One capable mini-PC at $1,200 and $70 per year in power serves all three for five years at roughly $1,550 total, compared to $5,000 to $7,200 in cloud subscriptions over the same period.
The cost comparison only holds if you use the hardware regularly. A $900 mini-PC is not worth the investment for someone who uses AI for ten minutes per week. Local AI hardware makes financial sense for daily users, multi-user households, and privacy-sensitive workloads where cloud services are not appropriate. For light or occasional use, a cloud subscription at $30 per month remains the more practical option.
What Costs More Than Expected
Several factors push real-world power costs above the nominal device figures. NAS devices with four or more drives set to remain active (rather than sleeping) draw 5 to 10 watts more than the same device with aggressive drive sleep settings. If drives are spinning down between AI requests then spinning up again each time, that cycling adds wear but saves power. Choosing between continuous drive spin and sleep-on-demand is a trade-off worth configuring deliberately.
Cooling is relevant in Australian summers. A device in an enclosed cabinet or poorly ventilated room runs hotter, which can increase effective power draw by 10 to 20 percent as processors throttle or fans ramp up to compensate. This is particularly relevant in Queensland, Western Australia, and New South Wales during summer when ambient room temperatures can exceed 30 degrees without air conditioning. Properly ventilated hardware runs cooler, draws less power, and lasts longer.
Always-on devices running multiple services also draw more than the AI inference figures suggest. A NAS simultaneously running Plex, Immich, Docker containers, and Ollama draws considerably more than a NAS running Ollama alone. The power figures in this guide assume the AI workload is the primary load on the device. For accurate cost tracking, measure actual draw with a plug-in watt meter rather than relying on manufacturer specifications, which are typically measured under minimal load conditions.
How much does it cost to run Ollama on a NAS in Australia?
If your NAS is already running 24/7 for file storage, the incremental cost of running Ollama is near zero. The processor and drives are already active. The additional power draw from a 7B model running occasionally is too small to measure meaningfully against the baseline device draw. If you are turning the NAS on specifically for AI inference, a 4-bay NAS at 25 watts continuous costs $57 to $105 per year depending on your state's electricity rate. See the Ollama on Synology setup guide for full configuration steps.
Which Australian state has the cheapest electricity for running local AI?
The ACT and Queensland have the lowest residential electricity rates in Australia, both typically under $0.32 per kWh for general usage tariffs. South Australia has the most expensive residential electricity at approximately $0.38 to $0.48 per kWh, which adds meaningful cost for any always-on hardware. If you are weighing up always-on vs on-demand operation for a dedicated mini-PC, the case for turning the device off when not in use is stronger in South Australia than in other states.
Is buying a mini-PC for local AI cheaper than paying for ChatGPT Plus?
Over five years, yes, for regular daily users. A capable mini-PC at $900 AUD including power costs totals approximately $1,100 to $1,200 over five years in NSW. Five years of ChatGPT Plus totals approximately $1,800. For multi-user households, the gap widens significantly. The local option requires upfront cost and the trade-off that local models are not as capable as the largest cloud models. For heavy daily users, local AI hardware pays off. For occasional users, a $30 per month cloud subscription remains more practical.
How do I measure the actual power draw of my AI hardware?
A plug-in watt meter (also called an energy monitor or power meter) is the most accurate approach. Models like the Powertech PM2300 or similar are available from Jaycar and similar retailers in Australia for approximately $25 to $50. Plug the meter between the wall socket and the device, let it run for 24 hours under typical usage, and read the kilowatt-hour consumption directly. Manufacturer idle figures are measured under minimal load conditions and often read 20 to 40 percent lower than real-world figures where background services, drive activity, and cooling all add to the draw.
Does running AI inference all day shorten hardware lifespan?
Sustained inference workloads run hardware hotter and harder than typical NAS storage workloads. Mini-PCs purpose-built for compute handle sustained load well if ventilation is adequate. NAS hardware is designed for 24/7 storage operation at light compute loads. Running heavy sustained inference on a NAS processor will accelerate wear compared to storage-only use. If running inference on a NAS, schedule heavy batch jobs for cooler parts of the day and ensure the device has adequate airflow. For continuous heavy inference workloads, a dedicated mini-PC with proper cooling handles the load more gracefully than a NAS not designed for that purpose.
Deciding between a NAS and a dedicated mini-PC for local AI? The full comparison covers performance, RAM ceilings, real AU costs, and which platform fits which use case.
Read the Mini-PC vs NAS Guide