[drafted by project agent, edited by me, by hand]
Ask what local AI costs and the conversation usually jumps straight to the hardware bill. The other side answers with an API price per million tokens. Both numbers are real. Neither tells you what it costs to keep a local box available, or what one more answer adds to the meter.
So we measured ours.
The short version is this:
On our hardware, a typical local answer costs about $0.00003 in marginal electricity at the measured operating point — roughly 0.003¢. Keeping the box powered and ready is the larger number: about $10 a month running 24/7 at our all-in reference rate.
Those are not universal prices. They are numbers for one box, one model, one serving mode, one workload, and one electricity rate. The useful part is the shape of the cost, and the method is simple enough to repeat.
The box and the meter
The measured machine is an Intel Arc Pro B60 attached to a UM890 Pro host through an OCuLink dock. We measured both halves at the wall with two smart plugs: one for the host and one for the card, dock, and dedicated power supply.
The local model for the benchmark point was a Qwen3.6-35B-A3B Q4_K_M served with llama.cpp, single stream. The wall-meter benchmark used a Tapo P115 with stated accuracy of approximately ±2%.
The monthly number came from a different, longer measurement: both plugs ran for about 25.3 days with no recorded off-time.
That distinction matters. A short benchmark tells you about the energy used while answering. A month-long plug reading tells you what the machine costs when it is part of the room, including the time it spends waiting.
What the month-long reading showed
Measured energy, about 25.3 days - 35.99kWh
Average draw over that period - 59.2W
Projected 31-day energy - about 44 kWh
All-in reference rate used for the conversion - $0.2208/kWh
Projected monthly electricity cost - about $9.72
Average cost per hour, running 24/7 - about 1.3¢
The plain-English version is under $10 a month to run 24/7, at this rate and for this measured rig. It works out to about 29¢ a day.
The average draw is close to the measured idle floor because the box is not generating continuously. It spends much of its life powered on and waiting. That is the idle tax, and it is the number a marginal-only calculation leaves out.
What one more answer adds
The marginal answer number comes from the locked wall-meter operating point, not from dividing the monthly bill by an arbitrary number of prompts.
At the balanced chat operating point, the whole box measured about 799 output tokens per watt-hour in the lock-grade run. A served 8K single-stream operating point measured about 671 tokens per watt-hour. The energy methods agreed to better than 1% on the benchmark windows; the absolute meter accuracy remains the relevant ±2% bound.
Using the recorded benchmark conversion, the preliminary marginal estimate is:
about $0.00003 per answer at $0.17/kWh — approximately 0.003¢.
Using the higher all-in rate from the measured household bill, $0.2208/kWh, the same operating-point estimate scales to roughly $0.00004 per answer. We are rounding this as an order-of-magnitude field number, not claiming that every answer has the same length or energy profile.
A short answer, a long answer, a cold uncached prompt, and a decode-heavy chat do not cost the same. The benchmark itself showed three regimes:
READ: about 297 tok/Wh, cold and uncached, with an 8,008-token input prefilled per answer.
CHAT: about 799 tok/Wh, the balanced middle case.
WRITE: about 1,020 tok/Wh, a decode-dominated ceiling.
That is why the honest sentence is “on our hardware, about X,” not “local AI always costs X.”
The part that changes the answer: whether the box is already on
The marginal number is the cost of doing one more job while the machine is already running. It does not pay for the hardware, the dock, the host, or the hours spent waiting.
If the box is already powered for other work, the extra electricity for one answer can be close to the marginal number. If the only reason to keep it running is one occasional question, the idle draw becomes the dominant cost.
That gives local AI two different economic stories:
High use: the fixed cost of keeping the box on is spread across more answers. The marginal electricity is small.
Low use: the idle tax can matter more than the answers. A box that sits waiting all month is not “free” just because each generated answer uses a fraction of a cent.
Neither story is the whole answer. You need both.
What this does not include
These figures are an electricity floor plus a measured operating-cost view. They do not include:
the purchase price or depreciation of the hardware;
maintenance, replacement parts, or downtime;
the operator’s time;
networking, storage, or other household infrastructure;
the quality of the answer compared with a cloud service;
a universal electricity rate.
The measured monthly figure includes the actual all-in rate used for our internal conversion. Readers should substitute their own rate. The published method should carry the watt-hours and assumptions without exposing a location-specific utility bill.
So, what does local A.I. cost?
On this box, at this operating point:
One additional answer: about $0.00003–$0.00004 in electricity, or roughly 0.003–0.004¢, depending on the reference rate used.
Keeping the complete rig powered 24/7: about $10 a month at the measured all-in rate.
The practical warning: at low usage, idle power matters more than the cost of the individual answer.
That is the number we can stand behind: not a promise for every local-AI build, but a measured answer for ours, with enough method attached that someone else can check the shape against their own wall meter.
The cost is small. The assumptions are not.
The method
Whole rig: UM890 Pro host plus Intel Arc Pro B60, OCuLink dock, and dedicated PSU.
Monthly telemetry: two smart plugs, approximately 25.3 days, 35.99 kWh total, 59.2 W average.
Projected monthly conversion: approximately 44 kWh × $0.2208/kWh = approximately $9.72.
Benchmark: Tapo P115, approximately ±2%; Qwen3.6-35B-A3B Q4_K_M; llama.cpp; single stream; temperature 0; lock-grade run dated 2026-07-15.
The marginal per-answer figure is preliminary for this article’s framing. It is not a universal tariff or a fully loaded total cost of ownership.