AU Power Cost of Running Local AI 24/7 — What It Really Costs by State

Running local AI inference 24/7 in Australia costs between $55 and $210 per year in electricity, depending on your hardware and which state you are in. A NAS running a 7B model in low-power mode costs far less than a desktop GPU rig running continuous inference. The difference is not just the hardware. It is the rate your distributor charges, and South Australian users pay almost double what ACT residents do per kilowatt-hour.

Australian Electricity Rates by State (2026)

Australian electricity prices vary significantly by state. These are typical residential flat-rate tariffs as of early 2026. The actual rate on your bill depends on your retailer, tariff type, and whether you are on a controlled load or time-of-use plan. Always check your latest bill for your specific rate.

South Australian users pay the most in the developed world for residential electricity. The rate difference between SA and QLD translates to an extra $30-50/year for the same NAS running the same workload. It is a real factor when evaluating whether local inference is cheaper than paying for cloud AI access over the long term. Use the NAS Power Cost Calculator to enter your exact tariff and hardware wattage.

How Much Power Does Local AI Inference Actually Draw?

Power consumption during AI inference depends on three things: the CPU or GPU doing the work, whether you are running inference continuously or on demand, and whether the system has fully spun up its drives. The figures below are measured or vendor-confirmed idle and load values for hardware commonly used for local AI in Australia.

NAS Hardware. Power Under AI Load

The N97-based Synology models (DS225+, DS425+) are the most power-efficient for light AI workloads. Simple document summarisation, small 3B models, or Immich facial recognition. The AMD Ryzen V1500B in QNAP's TS-473A and TS-873A offers meaningfully more inference throughput per second, but the idle floor is higher. If your AI workload is bursty rather than continuous, the Synology N97 platform makes more economic sense.

Mini-PC Hardware. Power Under AI Load

The Real Cost: On-Demand vs Continuous Inference

The 24/7 figures above are worst-case. Most home setups run AI inference on demand. A few queries an hour, not a constant stream. The actual power cost depends on your usage pattern:

• Continuous inference (rare): Always-on chatbot, 24/7 monitoring AI, continuous video analysis. Use the full 24/7 figure.
• Heavy on-demand (power user): 4-8 hours of active use per day. Multiply the load figure by 0.3-0.5. Plus idle cost for the remaining hours.
• Light on-demand (typical home): Queries throughout the day, mostly idle overnight. Real cost is typically 20-30% of the 24/7 figure. The idle floor dominates the bill.
• Photo indexing (weekly): Immich or Synology Photos AI runs a background job once per week. Power cost is negligible. A few cents per month.

For comparison, a ChatGPT Plus subscription costs $30 USD/month ($550-580 AUD/year at current exchange rates). A typical home NAS doing on-demand AI costs $15-45/year in electricity. Even a GPU-equipped desktop running 4 hours per day works out to $100-200/year. Still cheaper than a cloud subscription for heavy daily use. The NAS vs cloud AI cost comparison explores this in more detail.

Power Cost by Hardware Tier. Annual Estimates

These estimates assume the hardware runs at its AI load wattage for the active period and idle wattage for the remainder. Real consumption depends on RAID rebuild cycles, drive spin-up behaviour, and RAM heat. A NAS with 4 spinning HDDs adds 15-25W to the above figures when drives are active. SSDs add only 3-5W total.

How to Measure Your Actual Hardware

Estimates are useful for planning. For existing hardware, a $25-40 smart plug with power monitoring (TP-Link Tapo, Kasa) will give you real watt readings within minutes. Plug your NAS or mini-PC into the smart plug, let it idle for 10 minutes, then trigger an Ollama or Immich AI job and watch the wattage in the app. That is your actual idle and load figure. Multiply by your tariff rate from your latest bill and extrapolate.

The NAS Power Cost Calculator lets you enter your measured wattage and your specific tariff rate (including time-of-use rates if applicable) and will calculate annual, monthly, and hourly costs. It also includes preset wattage values for all current NAS models stocked in Australia.

Key Mistakes People Make When Estimating AI Power Costs

• Using peak TDP instead of actual load wattage. A CPU's 45W TDP is the thermal ceiling, not the steady-state power draw. AI inference on a Ryzen V1500B typically draws 30-45W, not the 54W TDP. Measure, do not guess.
• Forgetting the drive stack. A 4-bay NAS with spinning HDDs adds 15-25W when drives are active. SSDs change this equation completely. A 4-bay all-SSD NAS adds only 3-6W.
• Assuming 24/7 when usage is bursty. Most Immich installs do nightly AI indexing for 30-60 minutes. At that rate the annual power cost is under $5. People quote 24/7 figures for workloads that run a fraction of that time.
• Using US electricity rates. Australian residential rates are 2-3x US average rates. Any comparison article that uses US power costs ($0.12-0.15/kWh) will significantly understate the Australian operating cost.

Australian Buyers: What You Need to Know

Australia has some of the highest residential electricity rates in the world, which changes the economics of local AI compared to comparable setups in the US or Europe. Key AU-specific considerations:

• SA is the worst-case state. At $0.42-0.45/kWh, a GPU rig running 24/7 in Adelaide costs $700-800/year in electricity alone. That changes the break-even calculation against cloud AI significantly.
• Solar households can offset this. If you have rooftop solar and can run inference jobs during daylight hours, the effective electricity cost drops to your feed-in tariff displacement rate. Typically $0.06-0.10/kWh. That changes a $180/year mini-PC cost to $27-45/year for daytime use.
• Time-of-use tariffs matter. Running batch AI jobs (video transcription, photo indexing) during off-peak windows (11pm-7am at $0.10-0.15/kWh in some states) cuts costs by 50-70% versus peak rates.
• NBN upload limits mean local inference is not just a cost consideration. For Australian users sending large prompts, documents, or images to cloud AI APIs, the upload overhead is non-trivial on typical NBN connections. See the NBN upload limits and cloud AI analysis for the latency and throughput case for local inference.

Related reading: our NAS buyer's guide, our NAS power consumption guide, and our NAS vs cloud storage comparison.

Use our free AI Hardware Requirements Calculator to size the hardware you need to run AI locally.

How much does it cost to run Ollama on a NAS 24/7 in Australia?

A typical NAS running Ollama continuously draws 30-55W under load. At Australian residential rates ($0.28-0.45/kWh depending on state), that works out to $65-210 per year for constant 24/7 inference. Most users run inference on demand rather than continuously, which brings real costs down to $15-60/year. Use a smart plug with power monitoring to measure your specific hardware.

Is local AI cheaper to run than a ChatGPT Plus subscription in Australia?

For most home users, yes. A ChatGPT Plus subscription costs approximately $550-580 AUD/year. A NAS running on-demand AI costs $20-80/year in electricity. Even a GPU-equipped mini-PC running several hours per day costs $150-300/year. The break-even depends on usage intensity and your electricity rate. The full comparison including hardware amortisation is in the NAS vs cloud AI cost article.

Does running local AI use significantly more power than a NAS idle?

Yes. A NAS idling draws 10-25W. The same NAS running active AI inference draws 30-60W. Roughly double to triple the idle consumption. The increase depends on how hard the CPU is working: small 3B models on an N97 processor draw less additional power than a 7B model on a Ryzen V1500B. Drive activity during inference also contributes, particularly on HDDs.

Which state in Australia has the highest electricity cost for running AI hardware?

South Australia consistently has the highest residential electricity rates in Australia, typically $0.38-0.45/kWh. This means running the same 50W NAS costs around 40-60% more per year in SA than in Queensland or ACT. If you are in SA, time-of-use tariffs and solar offset are worth investigating before committing to a power-intensive AI setup.

Do SSDs reduce AI inference power costs on a NAS?

Yes, substantially for the drive component. Each spinning HDD in a NAS draws 5-8W when active. A 4-bay HDD array adds 20-32W to your total. NVMe SSDs draw 3-5W total for a 4-bay array, and 2.5-inch SATA SSDs are similar. If your NAS supports M.2 NVMe caching or all-SSD bays, the drive contribution to your power bill drops from a significant factor to near-negligible. The CPU remains the dominant power draw during AI inference regardless of storage type.

Can I reduce AI inference power costs by scheduling jobs during off-peak hours?

Yes. If you are on a time-of-use electricity tariff, running batch AI jobs overnight (typically 11pm-7am in most states) can cut the effective rate by 50-70%. Ollama and Open WebUI do not natively support scheduled jobs, but you can use cron on the host system to trigger inference tasks. This is most relevant for batch workloads like Immich AI photo indexing, video transcription, or document processing where real-time response is not needed.