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Compare the total cost of running AI models locally on your own hardware versus paying for cloud API access. Find your break-even point and calculate long-term savings.
Quick Scenarios
Enter a hardware price and at least one API price or subscription to calculate.
Select your hardware and an API model, then adjust usage parameters to see your ROI projection.
The AI hardware ROI calculator is a free tool that projects the break-even month between owning a local AI workstation and paying for a cloud API. It adds the upfront GPU MSRP to a monthly electricity bill (TDP × hours × kWh rate), compares that running total against blended cloud API spend (per-token usage × daily volume + any subscription), and surfaces the month the cumulative lines cross.
The calculator supports five modalities — text, image, video, audio, and embedding — each with its own usage unit (tokens/day, images/day, video seconds/day, audio seconds/day, embeddings/day). Pick a hardware product and an API model from the dropdowns, set your usage volume on a log-scale slider, and the amortization chart updates in real time with cumulative cost curves, a break-even marker, and a savings zone shaded after that month.
Pricing data is live where possible. For text models, the input/output rates auto-sync from OpenRouter every day. For the other modalities, prices come from the manually maintained reference-model directory. Electricity is the one input you should localize to your region — the default $0.12/kWh is roughly the US average; European rates can be 2–3× higher.
Add a Third Column
The ROI calculator compares buying vs API. Add a Rent column to see whether renting a cloud GPU on RunPod or Vast.ai beats both at your usage, with live pricing on every column.
Live cloud GPU rental rates across RunPod and the Vast.ai marketplace.
Per-token prices for 350+ hosted models — the same feed driving the API column here.
Before you compare cost, confirm the hardware can actually run the model you want.
Once the math says "buy", get a curated parts list and pre-built option side by side.
The calculator builds two cumulative-cost curves over your projection horizon. The local hardware curve starts at the GPU MSRP and climbs at the rate of monthly electricity (TDP watts ÷ 1000 × hours/day × 30.44 days × $/kWh). The cloud curve starts at zero and climbs at the rate of monthly API usage (daily volume × per-unit price × 30.44) plus any monthly subscription fee. The break-even month is the first month the cloud cumulative exceeds the local cumulative.
Only the GPU draw is modeled, not the rest of the workstation. We use the card’s rated TDP (thermal design power) as a worst-case continuous draw — actual inference draws are usually 70–90% of TDP. Multiply by hours of active use per day and your local kWh rate. The default $0.12/kWh is roughly the US residential average; lookup your utility bill for an accurate number.
Hosted AI APIs charge different rates for input (prompt) and output (completion) tokens. Output is typically 2–5× more expensive because generation is the compute-heavy step. The calculator combines the two at a weighted ratio (default 70% input, 30% output) that approximates typical chat and coding workloads. Adjust the ratio on the slider to reweight for input-heavy retrieval or output-heavy generation tasks.
Yes. Add the monthly subscription fee to the "subscription" field and the cloud curve climbs by that amount each month on top of per-token usage. Useful for users who already pay $20/mo for ChatGPT Plus and are deciding whether the unlimited-tier convenience justifies skipping a local GPU.
Two common reasons: low usage and frontier-model dependency. If you only spend $5–10/mo on tokens, no GPU pays off inside a sensible horizon. And if you depend on GPT or Claude quality, no local open-weight model matches that grade today — staying on cloud is the right call until open models close the gap. Use the gap tracker to monitor that.
No, MSRP is treated as a sunk cost. In practice a used RTX 4090 holds 60–70% of MSRP after 2 years, which would shift the break-even forward by 6–12 months in most scenarios. The conservative full-MSRP assumption avoids overstating the case for buying.
