Written by Jakub Rusinowski · Last updated 2026-07-08 · Prices verified 2026-03-01
For heavy daily use (about 2 million tokens per day), running an open-weight model on a used RTX 3090 build costs roughly $76/month all-in (24-month hardware amortization plus electricity), while the same volume on GPT-4o costs about $285/month — so the hardware pays for itself in around 5 months. At light usage (under ~200k tokens/day) cloud APIs stay cheaper, because the hardware never earns back its up-front cost.
The cost dimension, side by side — what each dollar actually buys you.
| Dimension | Local | Cloud |
|---|---|---|
| Up-front cost | $500–2,900 for a capable build (used RTX 3090 tier: ~$1,240) | $0 — pay as you go |
| Marginal cost per 1M tokens | Electricity only: ~$0.30–0.60 at $0.15/kWh | $0.18 (hosted Llama 8B) to $15+ (frontier output tokens) |
| Cost predictability | Flat — usage spikes cost nothing extra | Linear with usage; spikes show up on the invoice |
| Model quality ceiling | 70B-class open models (24–48 GB VRAM) | Frontier models (GPT-4o, Claude, Gemini Pro) |
| Depreciation / lock-in | Hardware depreciates; GPUs hold resale value unusually well | No asset, no resale — spend is gone |
| Hidden costs | Your setup time; occasional maintenance | Rate-limit engineering, egress, retries, price changes |
Heavy daily use: ~2M tokens/day (a busy assistant, batch jobs, or a small product) — 2M tokens/day, Used RTX 3090 24GB Value King vs GPT-4o (OpenAI), electricity $0.15/kWh. Adjust every input in the interactive calculator on this page.
| Cloud cost / month | $285 (GPT-4o, $2.5/M input + $10/M output) |
| Local cost / month (24-mo TCO) | $76.11 — $24.44 electricity + hardware amortization |
| Hardware up-front | $1,240 (Used RTX 3090 24GB Value King) |
| Break-even | Month 5 — cumulative cloud spend passes local |
Estimates: 70/30 input/output mix, 24-month amortization, no resale value, load-time electricity only. Cloud prices last verified: 2026-03-01. Hardware street price checked: 2026-07-06.
Every local-vs-cloud cost argument reduces to three numbers: your daily token volume, the per-token price of the cloud model you would otherwise use, and the up-front price of hardware capable of a comparable job. Everything else — electricity, amortization period, input/output mix — moves the answer by weeks, not months.
Cloud pricing is public and precise. As of our last verification, OpenAI charges $2.50 per million input tokens and $10.00 per million output tokens for GPT-4o, Anthropic charges $3.00/$15.00 for Claude Sonnet, and hosted open models are dramatically cheaper — Together.ai serves Llama 3.1 8B at $0.18 per million tokens in either direction. That spread matters: the honest cloud comparison for a local 8B model is the $0.18 hosted version of the *same model*, not a frontier model it can't match.
On the local side, the dominant cost is the GPU. A used RTX 3090 with 24 GB of VRAM — still the best value in local AI, as our GPU buyer's guide argues — anchors a complete build at about $1,240 (street prices, checked July 2026, see /build). That machine runs 30B-class models at Q4 quantization: genuinely useful quality, a tier below frontier.
Take a heavy user: 2 million tokens a day at a 70/30 input/output split.
Break-even: $1,240 ÷ ($285 − $24) ≈ 4.8 months. After that, the marginal cost of every additional token is electricity — roughly $0.40 per million tokens, an order of magnitude below even budget cloud tiers.
Now the honest inversions. Drop the volume to 200k tokens/day and the cloud bill falls to ~$28/month; break-even stretches past three and a half years — longer than you should plan around a used GPU. Or keep the volume but switch the cloud comparison to GPT-4o Mini ($0.15/$0.60): the cloud bill is ~$17/month and local never breaks even on cost alone. If Mini-class quality genuinely covers your workload, cloud wins the pure cost argument at almost any volume.
The calculator below uses the same math as this page — one shared module, not marketing arithmetic. Assumptions: 24-month amortization, zero resale value (conservative — 3090s resell well), electricity billed only for load time, and no cloud volume discounts. It ignores things that are real but unquantifiable per reader: your time to set up (an evening with Ollama, realistically), the value of offline capability, and the quality gap between a 30B open model and a frontier API — which for many workloads (summarization, extraction, internal chat, RAG over your own docs) is smaller than the price gap implies. See our /cost calculator for per-model comparisons across the whole library.
The trap in every cost comparison is holding quality constant when it isn't. A local Qwen 3 32B is not GPT-4o. But the right question is whether it clears *your* quality bar. If it does, you're comparing $0.40/M tokens against $4.75/M blended — and local wins by 10×. If it doesn't, no electricity math rescues a model that can't do the job; pay for the API. Run the model first (rent an hour on RunPod or check what your GPU can run) before buying anything.
Cost favors local surprisingly early for heavy users — a used RTX 3090 build recoups itself in about 5 months against GPT-4o at 2M tokens/day — but the comparison flips completely for light users or Mini-class workloads, where cloud is cheaper essentially forever. Be honest about your real daily volume and the cheapest cloud model that actually meets your quality bar; then the calculator gives you a date, not an opinion.
Not sure which tier fits? The build recommender maps budgets to complete part lists — or check what your existing GPU already runs for free.
Methodology & assumptions. All cost figures are estimates from one shared model (lib/costCompare.ts): cloud costs = tokens/day × published per-1M-token prices at a 70/30 input/output split × 30 days; local costs = hardware amortized over 24 months with no resale value + electricity for load time only at your rate, with machine count scaled when volume exceeds one machine’s throughput. Cloud prices carry per-entry source URLs and verification dates; hardware prices come from the curated /build catalog (street prices with check dates). Real bills vary with usage mix, discounts, and idle power — treat break-even months as directional, not contractual.