Local AI vs. a subscription: what the full cost shows

Local AI can have a tiny electricity cost without being cheaper overall than a subscription. Abhinav Raj reported an energy estimate of 14.9¢ per million generated tokens for one PC setup; a separate hardware-inclusive example put local use at $58.60 a month and below only its $150-a-month API scenario. Raj’s report and Flavio Copes’s worked example measure different parts of the cost equation.

Electricity is one line in the local-AI budget. Hardware, workload and the kind of cloud service you compare it with can change the result.

What one local-AI electricity estimate covers

In an article published November 4, 2026, Raj described running the quantized Qwen3.6-35B-A3B model on a PC with an RTX 4070 Ti Super and Ryzen 5 7600X. The model’s reported size, 16.5 GB, exceeded the GPU’s 16 GB of memory, so experts from eight layers were offloaded to the CPU. Raj reported a combined CPU-and-GPU peak draw of 251.9 W during generation.

Using a projected 2026 U.S. residential electricity rate of 18.2¢ per kWh, Raj calculated generation electricity at 14.9¢ per million tokens. His calculation charged tokens at peak combined power draw and did not deduct idle power. Adding an assumed 100 W for other system components and power-supply losses raised the estimate to 20.8¢ per million tokens. Those figures describe electricity for that tested setup and method, not the cost of buying or depreciating a computer.

How hardware changes the monthly comparison

Copes’s separate illustration assumes an $1,800 RTX 4090 spread over 36 months, or $50 a month for hardware. For 500,000 generated tokens per day on an 8B Q4 model running at 40 tokens per second, he estimates electricity at $8.60 a month. That brings the local example to $58.60 monthly. The electricity estimate uses 400 W under load, 50 W of idle draw for eight hours a day, and $0.16 per kWh.

For the same example’s 15 million output tokens per month, Copes uses blended API rates of $0.40, $2 and $10 per million tokens:

At the $150 API cost, the example leaves $91.40 a month between API spending and local costs. Dividing the assumed $1,800 hardware purchase by that difference gives a payback period of about 19.7 months. At the two lower API costs, the monthly API bill is below the local estimate.

Volume also changes the calculation. In a separate scenario, Copes puts local costs at about $79 a month for two million tokens per day, against $120 a month for an API rate of $2 per million. The resulting $41 monthly difference gives a calculated hardware payback of about 43.9 months, longer than the assumed 36-month hardware life. Both results depend on the example’s inputs; they are not general hardware prices or guaranteed returns.

API prices and subscriptions are different comparisons

An API typically bills for token usage, while a subscription charges a plan fee and applies its own usage limits. AIMultiple’s pricing explanation distinguishes those billing models. An API rate per million tokens is therefore not a per-token price for a flat-rate subscription.

Raj also used a $20 subscription as an electricity-budget reference: at his projected rate, $20 corresponds to about 110 kWh, or roughly 436 hours of generation at 251.9 W. That converts a monthly dollar amount into electricity and runtime; it does not measure how much equivalent work a subscription provides.

For some users, cost is not the only reason to run models locally. In a Reddit discussion, one commenter described using a $20-per-month Claude account for difficult tasks and handling routine work with a local model. That is one user’s approach, not a general cost result. The discussion also includes commenters who value local AI for independence, privacy and control.