The Math That Makes You Rethink
Let's be concrete about 2026 prices:
| Subscription | Price (2026) |
|---|---|
| ChatGPT Business | $20/user/month (annual) or $25 (monthly), 2-seat minimum |
| Microsoft 365 Copilot | ~$30/user/month add-on (annual), on top of your M365 license |
| Typical team assistants | $20–$30/user/month |
Now multiply. A 20-person team at $25/user/month is $500/month — $6,000/year — every year, forever, and that's before the usage limits, the throttling at peak hours, and the seats you buy for people who barely use it. Industry data shows small businesses spending a median of $8,200 a year on AI tools — and that's just the subscriptions.
The Alternative: Own the Hardware, Own the AI
On-premise AI flips the model from "rent a seat forever" to "buy once, run free":
- Capable local setup (24GB+ VRAM GPU): $1,500–$4,000 once, plus $50–$300/month power.
- Small team server (single GPU): ~$30,000, serving a whole department.
- Or start with existing laptops: 8–16GB machines run 7–14B models for free — the hardware is already paid for.
After that, the marginal cost of another user is zero. No per-seat fee, no token meter, no overage invoice. Add a local RAG setup and the AI works on your documents — with citations — at no per-query cost.
⚠️ The honest caveat. The very latest frontier models are still API-only, and you own the maintenance — updates, monitoring, security. The trade is real. But for the ~95% of everyday work — drafting, summarizing, Q&A over your own files, translation — local models are good enough, and they get better every quarter.
What You Buy Beyond the Savings
🔒 Privacy
Documents and prompts never leave your control. That alone decides it for legal, medical, and proprietary work.
♾️ No limits
No daily caps, no throttling at peak hours, no "you've hit your usage limit." The AI works when you need it.
📴 Offline
Works without internet — on a plane, in a facility with restricted networks, anywhere.
🧮 Predictable cost
Capital cost once, small power bill after. Finance teams can actually budget it.
✅ Compliance
No third-party processing, no transfers, no vendor retention terms — the compliance answer for regulated data.
How to Calculate Your Break-Even
- Total annual subscription cost: users × price × 12 + known overages.
- Estimate on-premise cost: hardware (or $0 if you start on existing laptops) + power + ~10% of an admin's time.
- Compare. For a team of 5+ using AI daily, on-premise typically breaks even within one to two years — and then it's cheaper forever.
💡 The details matter: see What Is On-Premise LLM Deployment? Costs, Hardware, and When It's Worth It for hardware numbers, On-Premise LLM Deployment: A Practical Checklist for the build, and Local AI for Small Business for the adoption path.
Frequently Asked Questions (FAQ)
How much do per-seat AI subscriptions cost?
ChatGPT Business is $20/user/month billed annually ($25 monthly), Microsoft 365 Copilot adds about $30/user/month on top of your M365 license, and similar assistants run $20-30 per user per month. A 20-person team can spend $5,000-7,000+ per year before usage limits.
Is on-premise AI cheaper than subscriptions?
For steady, multi-user use, usually yes. A capable local setup costs $1,500-$4,000 once (or a small server ~$30K for a team) versus recurring per-seat fees that never stop. For spiky or low-volume use, subscriptions may win.
What else do I get besides cost savings?
Privacy (data never leaves your control), no usage limits or throttling, offline availability, unlimited model use, and compliance benefits. The market shift to on-premise — roughly 60% of the LLM market — reflects these advantages.
What are the downsides of on-premise?
You manage the infrastructure: hardware, updates, monitoring, and security. Model quality trails the very latest frontier APIs. For sensitive workloads, that trade is usually worth it — for exploratory use, less so.
How do I calculate the break-even?
Total your annual per-seat fees (users × price × 12), add usage overages, then compare against hardware cost plus ~$50-300/month power plus a little admin time. If you're a team of 5+ using AI daily, on-premise typically breaks even within a year or two.
💼 Want to cut the AI bill?
I design and deploy on-premise AI for teams — from single-workstation setups to shared department servers, through Haal Lab. Contact me for a break-even analysis of your workload.