Question 1

What exactly is a private LLM?

Accepted Answer

A private LLM is a large language model that runs on infrastructure you control rather than a third-party cloud. This ensures that your chat history, documents, and prompts are never used to train other models. By using Open WebUI on Opsily, you keep all data within a secure, isolated server environment. This setup effectively eliminates the risk of data leakage typical in public AI services. It is the best way to maintain absolute data sovereignty for your business.

Question 2

Can I use uncensored private LLM models with Open WebUI?

Accepted Answer

Yes, flexibility is one of the primary reasons teams choose a private LLM setup. You can connect to Ollama to run local models like Llama, or use API keys for models like Claude and GPT-4. This allows you to switch between models mid-conversation based on the task at hand. You can even run specialized, uncensored models for coding or research without changing your interface. Open WebUI serves as a single, unified bridge to all your AI intelligence.

Question 3

What are the real costs of running a private LLM on Opsily?

Accepted Answer

SaaS providers typically charge $20 to $30 per user every month for 'Enterprise' privacy features. For a team of 10, this can cost over $3,600 per year. Opsily offers a fixed-price model starting at much lower rates for the entire server. You can add as many users as your hardware can handle without extra fees. This shift from per-seat pricing to infrastructure-based pricing creates massive savings for growing teams.

Question 4

Can I self-host an LLM without technical expertise?

Accepted Answer

Yes. That's exactly what Opsily solves. Most self-hosting setups require Docker knowledge, SSL certificate management, and Linux administration. Opsily removes that entire layer. You log into Open WebUI, configure your models, and invite your team. Behind the scenes, we handle server provisioning, security updates, backups, and monitoring. If you can click a button, you can self-host on Opsily.

Question 5

What models can I run in a self-hosted LLM setup?

Accepted Answer

Open WebUI is model-agnostic. You can connect to Ollama and run local open-source models like Llama 3, Mistral, DeepSeek, or Phi. You can also use API keys for Claude, GPT-4, Gemini, or other cloud models. The power of self-hosting is choice. Don't like ChatGPT? Use Claude. Need an uncensored model for research? Install Llama locally. You can even mix local and API models in a single conversation and let your team choose which to use.

Question 6

How much server power do I need to self-host an LLM?

Accepted Answer

Depends on your model size and team size. Opsily Small ($20/mo) handles teams of 5-10 with smaller models like Phi or Mistral. Medium ($40/mo) runs larger models like Llama 3 for 20+ users. Large ($70/mo) supports very large models and concurrent users. If you're using API-based models (Claude, GPT-4), you don't need heavy compute — the API provider does the work. Start with Small, upgrade if you hit performance limits. We can help with rightsizing.

Question 7

Is self-hosting an LLM cheaper than ChatGPT Enterprise?

Accepted Answer

By a massive margin, yes. ChatGPT Enterprise costs $30 per user per month. For a 10-person team, that is $3,600 per year. For 50 people, it jumps to $18,000 per year. Opsily Small is $20/month flat, or $240/year for unlimited users on that instance. Even if you upgrade to Large ($70/month, $840/year), you are spending 95% less than ChatGPT Enterprise while getting more model flexibility and data control. The math is why companies switch.

Self-Hosted LLM: Behalten Sie die Kontrolle über Ihre KI

Die Self-Hosted LLM-Bewegung

Die SaaS-Falle

Die Self-Hosted-Alternative

Wer nutzt das?

Self-Hosted LLM vs. ChatGPT Enterprise

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Warum Opsily für Self-Hosted LLM?

Keine technischen Hürden

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Volle Datenkontrolle

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Self-Hosted LLM Preise

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Encrypted backups

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Self-Hosted LLM FAQs

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