Local AI or cloud AI? The 2026 cost comparison for SMEs
AI in a company almost always means a per-seat monthly subscription. But there is another way: your own AI server in-house that costs once and then serves everyone. This comparison runs both paths for 5, 10 and 25 users over three years, with real list prices and honest assumptions. As of July 2026.
Published on July 12, 2026 · Daniel Gläser
Two paths to AI in the company
Cloud AI such as Microsoft 365 Copilot, ChatGPT Business or Claude Team is billed per user per month: ready immediately, always the latest models, but the costs grow with every employee and run forever. Local AI flips the model: a server with a graphics card in your own building runs open language models, costs a one-off purchase plus electricity and care, and the data never leaves the premises. The interesting question is not which sounds better, but from what point which path pays off, and for which tasks the local models are good enough.
What cloud AI costs in 2026
The list prices of the three big business offerings, as of July 2026, each billed annually:
- Microsoft 365 Copilot (business add-on): 18.20 EUR per user per month plus VAT (promotional price 15.60 EUR for the first year when purchased between 1 July and 30 September 2026; 21.84 EUR with monthly billing). Requires an eligible Microsoft 365 business plan, whose costs come on top. The Business Standard plus Copilot and Business Premium plus Copilot bundles sit at 20.36 and 27.73 EUR respectively.
- ChatGPT Business: since 2 April 2026, 20 USD per user per month billed annually (25 USD monthly), minimum 2 seats. Advanced features such as deep research or image generation additionally run on usage-based workspace credits.
- Claude Team (Anthropic): standard seat 20 USD per user per month billed annually (25 USD monthly), premium seat with five times the usage 100 USD, for teams of 5 to 150 people, Claude Code included.
| Team size | M365 Copilot add-on | ChatGPT Business | Claude Team (standard) |
|---|---|---|---|
| 5 users | 3,276 EUR | 3,600 USD | 3,600 USD |
| 10 users | 6,552 EUR | 7,200 USD | 7,200 USD |
| 25 users | 16,380 EUR | 18,000 USD | 18,000 USD |
What a local AI server costs
Local AI needs one thing above all: fast graphics memory. In its October 2025 hardware overview, heise concludes that local models have become genuinely usable, and names as entry points a used RTX 3090 with 24 GB of VRAM from around 700 EUR or complete systems with AMD Ryzen AI Max+ 395 from about 1,800 EUR. Memory bandwidth is the most important performance factor, not raw compute.
| Item | Assumption | Cost |
|---|---|---|
| Hardware | Complete system of the Ryzen AI Max+ class or a server with a used 24 GB GPU | approx. 1,800 to 3,000 EUR one-off |
| Electricity | 150 W average, 24/7, 0.30 EUR per kWh, 3 years | approx. 1,200 EUR |
| Setup and care | Installation, updates, monitoring (in-house or via a provider) | depends on the model, from a few hours per quarter |
| Software and models | Ollama or vLLM plus open models | 0 EUR license costs |
That yields a simple rule of thumb: a local server lands at roughly 3,000 to 4,500 EUR over three years plus care. For 5 users that is more expensive than any cloud subscription. From around 10 users it plays in the same league, from 25 users clearly below it, because the cloud bill keeps growing per head and the local one does not.
Which models are genuinely usable locally in 2026
The cost comparison is useless if the quality is not there. The honest assessment: the best cloud models remain ahead of the open ones, especially for complex reasoning. For typical SME tasks such as summarising, rewriting, email drafts, minutes and searching your own documents (RAG), open models are now genuinely usable according to the heise overview. Among those named:
- Qwen 3 in several sizes, from the compact 4B model to the coder model with 30 billion parameters.
- Gemma 3 12B from Google, which can also analyse images.
- Mistral Small 3.2 with 24 billion parameters.
- GPT-OSS 120B from OpenAI, which at around 63 GB already demands premium hardware.
Rule of thumb for hardware choice
The bigger the model, the more fast memory you need. 24 GB of graphics memory covers the mid-size model class that handles most document tasks well. If you want the very large open models, you need considerably more expensive hardware, and should first check whether the quality jump even matters for the task.
Data protection: when local is the better choice
With local AI, prompts and documents never leave the building: no data processing agreement for model usage, no third-country transfer, no dependence on adequacy decisions. For medical practices, law firms and anyone with sensitive customer data, that is the strongest argument. Cloud AI can be used in a GDPR-compliant way, but demands homework: the right tier and region, a processing agreement and clear team rules. Which provider options exist for that, from Azure OpenAI with the EU Data Zone via OpenAI's EU data residency to the German IONOS AI Model Hub, is covered in the guide Using ChatGPT and co. GDPR-compliantly.
Hybrid in practice: the best of both worlds
In practice it is rarely either-or. The pattern that works: sensitive and recurring tasks run locally (document search, internal summaries, receipt processing), peak tasks with high quality demands run in the cloud, on a proper tier with a processing agreement. That keeps the cloud bill small, because not every employee needs a full-time subscription, and the delicate data stays in-house.
These are exactly the setups I build as part of my AI automation services: from sizing the AI server via model selection to connecting the models to your documents and workflows. Which tasks are concretely worth it is shown in the article on AI use cases in SMEs.
Sources
- Microsoft: Microsoft 365 Copilot Preise Deutschland
- OpenAI: ChatGPT Business (Preise und Funktionsumfang)
- OpenAI: Datenresidenz in Europa (Februar 2025)
- Anthropic: Claude Preisübersicht (Team und Enterprise)
- heise: Lokale KI-Modelle sind jetzt brauchbar, und auf dieser Hardware laufen sie (Oktober 2025)
- IONOS: AI Model Hub (Open-Source-Modelle, in Deutschland gehostet)
- Microsoft Learn: EU Data Boundary (Übersicht)
- Bitkom: Unternehmen beschäftigen sich mit KI (März 2026)
This article is carefully researched guidance, not legal or tax advice. For binding information, please consult your tax advisor or lawyer.
Frequently asked questions
What does Microsoft 365 Copilot currently cost?+
18.20 EUR per user per month plus VAT with annual billing (promotional price 15.60 EUR for the first year when purchased between 1 July and 30 September 2026; 21.84 EUR monthly), plus the required Microsoft 365 base license. The bundles with Business Standard or Premium sit at 20.36 and 27.73 EUR. As of July 2026, source: Microsoft's pricing page.
What does ChatGPT cost for companies?+
ChatGPT Business costs 20 USD per user per month with annual billing since 2 April 2026, 25 USD with monthly billing, from 2 seats. Advanced features additionally run on usage-based credits. Enterprise pricing is sales-only. As of July 2026.
From what size does an own AI server pay off?+
As a rule of thumb from the example calculation: from around 10 users a local server plays in the same cost class as cloud subscriptions over three years, from around 25 users it sits clearly below. The precondition is that the tasks can be handled well with open models, otherwise you pay twice.
What hardware does local AI need in an SME?+
Above all fast graphics memory. As entry points heise names a used RTX 3090 with 24 GB from around 700 EUR or complete systems with Ryzen AI Max+ 395 from about 1,800 EUR; memory bandwidth is the key performance factor. That covers the mid-size model class that handles document tasks.
Are local models as good as ChatGPT?+
No, the cloud providers' flagship models remain ahead, especially for complex reasoning. For summaries, drafts, translations and searching your own documents, open models such as Qwen 3, Gemma 3 or Mistral Small are now genuinely usable. What decides is the concrete use case, not the benchmark.
Is local AI automatically GDPR-compliant?+
It removes the biggest construction sites, because no data flows to third parties: no processing agreement for model usage, no third-country transfer. The remaining GDPR duties still apply, such as purpose limitation, access control and, depending on what is processed, a data protection impact assessment.
Cloud subscription, own server, or both?
I run both paths for your user count and your tasks, build the AI server where it pays off, and connect the models to your documents and workflows. GDPR-compliant, from Chemnitz for SMEs in Saxony and across Germany.
Daniel Gläser
Owner of Gläser IT-Solutions, Chemnitz
I build software and run IT infrastructure for small and medium businesses, from the first analysis to day-to-day operations. Everything here comes from real projects and is backed by sources.
