Last month I ran Llama 3.3 70B through a cloud GPU for a coding project. Seven days at eight hours a day, priced at our steepest listed cloud rate ($3/hr in the dataset — think H100-class), rings up to $184. The same week on a local RTX 4090-class rig (our High-End AI Workstation build is $3,672) cost me about $2 to $4 in electricity at typical US residential rates — order-of-magnitude, not a utility bill audit.
The math isn't subtle.
This guide uses real pricing from 2 cloud providers and real build costs from OwnRig's 14 curated systems. No hand-waving, no "it depends." Just numbers.
$876
Per year for the cheapest cloud GPU at 8 hours/day
That same money buys a local build that lasts 3 to 5 years
What cloud actually costs
Cloud GPU pricing looks cheap by the hour. It isn't cheap by the month. Here's what 2 providers charge, calculated out to the timeframes that actually matter:
| Provider | GPU | VRAM | $/Hour | $/Month (8h/day) | $/Year (8h/day) |
|---|---|---|---|---|---|
| Vast.ai | RTX 3090 | 24 GB | $0.30 | $72 | $876 |
| RunPod | RTX 3090 | 24 GB | $0.44 | $106 | $1,285 |
| Vast.ai | RTX 4090 | 24 GB | $0.55 | $132 | $1,606 |
| Vast.ai | A6000 | 48 GB | $0.59 | $142 | $1,723 |
| RunPod | RTX 4090 | 24 GB | $0.69 | $166 | $2,015 |
| Vast.ai | A100 80GB | 80 GB | $1.15 | $276 | $3,358 |
| RunPod | A100 80GB | 80 GB | $1.64 | $394 | $4,789 |
| RunPod | H100 80GB | 80 GB | $3.29 | $790 | $9,607 |
Look at the yearly column. Even at $0/hour, running AI 8 hours a day costs $876 per year. At the high end? $9,607. That's not a compute bill. That's a car payment.
What local hardware costs: once
Here are OwnRig's curated builds. Every price is the complete system: GPU, CPU, motherboard, RAM, storage, cooler, PSU, and case. You buy it once. You own it.
| Build | Tier | VRAM | Total cost | Models it runs |
|---|---|---|---|---|
| Starter AI Desktop | Budget | 12 GB | $582 | 6 |
| Budget AI Desktop | Budget | 12 GB | $753 | 7 |
| Budget Home AI Server | Budget | 16 GB | $1,162 | 7 |
| Mid-Range AI Workstation | Mid-range | 16 GB | $1,228 | 8 |
| Silent Mini-ITX AI Box | Mid-range | 16 GB | $1,253 | 8 |
| Compact SFF AI Build | Mid-range | 12 GB | $1,473 | 5 |
| AMD AI Powerhouse | High-end | 24 GB | $1,818 | 7 |
| Mid-Range Home AI Server | Mid-range | 24 GB | $1,892 | 9 |
| AI Builder Workstation | Mid-range | 24 GB | $2,902 | 10 |
| High-End AI Workstation | High-end | 24 GB | $3,672 | 8 |
| High-End Home AI Server | High-end | 48 GB | $3,842 | 12 |
| Mac Studio AI Builder | High-end | 128 GB | $3,999 | 6 |
| Next-Gen AI Workstation | Extreme | 32 GB | $4,032 | 6 |
| Extreme AI Workstation | Extreme | 48 GB | $4,171 | 8 |
The break-even math
Divide your build cost by your monthly cloud spend. That's how many months until local is free. Here's what that looks like at $0/hour (the cheapest cloud option):
Casual user: 2 hours per day
Monthly cloud cost: ~$18. A $582 budget build takes 32 months to break even. For casual use, cloud might be simpler. But you're giving up privacy, offline access, and zero-latency responses.
Developer: 8 hours per day
Monthly cloud cost: ~$72. A mid-range build at $1,228 breaks even in 17 months.
This is where local wins decisively.
Power user or team: 12+ hours per day
Monthly cloud cost: ~$108. Even a high-end build at $1,818 breaks even in 17 months. For always-on workloads, local isn't just cheaper. It's dramatically cheaper.
17mo
Break-even for a developer using AI 8 hours/day
After that, you're running AI for roughly $10/month in electricity
Beyond cost: why local wins
Cost is the headline. But it's not the whole story.
- Privacy: Your data never leaves your machine. No API logs, no third-party access. For code, medical data, or legal work, this isn't optional.
- Latency: Zero network round-trip. Responses start generating instantly. Once you experience it, cloud latency feels broken.
- Availability: No outages, no rate limits, no service degradation. Your hardware doesn't go down because someone else's workload spiked.
- No metering: Run as many queries as you want. Generate as many images as you need. There's no bill at the end.
- Offline: Works on planes, in secure facilities, anywhere without internet.
When cloud still wins
I'm not going to pretend local is always the answer. Cloud is better when:
- You use AI occasionally. A few times a week? Cloud costs pocket change. Don't build a PC for $3 per month in compute.
- You need the largest models. 100B+ parameter models need multiple GPUs. Cloud makes this accessible without building a server.
- You're serving production traffic. Scaling to many concurrent users needs cloud infrastructure. Local is for personal and team use.
- You're experimenting. Trying 20 different models for an afternoon is easier on cloud than downloading 800 GB of model files.
Our recommendation
If you use AI models more than 4 hours a day, build local. Start withBuild My Rig to match your models and budget to the right hardware. You'll break even in months and run AI for years.
If you use AI a few times a week, stick with cloud. It's simpler, cheaper at low usage, and you can always build later when your usage grows.
