Local LLM AI Workstations
Buy Local LLM Workstations – Run LLMs Locally and Securely
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Local LLM KI Workstations
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Local LLM AI Workstations: Language Models Locally Instead of in the Cloud
With a Local LLM AI Workstation from MIFCOM, you can run large language models such as Llama, Mistral, or Qwen directly on your own hardware. Your prompts and documents never leave your network, there are no ongoing API costs, and response times do not depend on external services. You configure each system component by component to suit your specific use case; every system is manufactured and tested in Germany.
Graphics memory is key: it determines which model sizes run smoothly
The most important factor for local inference is graphics memory. If the model fits entirely into the VRAM, the output speed remains high; if it has to be swapped out, the speed drops noticeably. More graphics memory not only allows for larger models but also supports longer contexts when working with extensive documents. An overview of our recommendations:
Our recommendations for local LLMs:
| Model Class | Optimized Models | Recommended GPU | RAM |
| Compact & Agile (3B–8B) | Llama 3.1 8B, Mistral 7B | GeForce RTX 5080, 16GB VRAM | 32GB |
| Mid-range (up to 32B) | Qwen 32B, Gemma 27B | GeForce RTX 5090, 32GB VRAM | 64GB |
| Large, quantized (70B class, 4-bit) | Llama 3.3 70B (4-bit) | RTX PRO 5000 Blackwell, 48GB VRAM | 128GB |
| Maximum: large models & long contexts | 70B+ with high precision, RAG with large documents | RTX PRO 6000 Blackwell, 96GB VRAM | 128 GB |
Ready to go right away with Ollama, LM Studio, and more
Your workstation serves as the foundation for common inference environments such as Ollama, LM Studio, or llama.cpp. This allows you to load models with just a few commands, run private chatbots and programming assistants, and integrate local models into your own applications via API.
Data Protection and Cost Control for Businesses
In professional settings in particular, there are two key advantages to using local language models: Sensitive data such as contracts, source code, or patient records remain on-premises, which significantly simplifies compliance with the GDPR. And instead of monthly billing per token, you make a one-time investment in hardware that then runs indefinitely. If you want to not only run models but also fine-tune them with your own data, our AI Development Workstations provide the ideal foundation for fine-tuning with LoRA and QLoRA.
Which Local LLM AI Workstation Is Right for You?
Choose your system based on the largest model you plan to use regularly, and allow for extra graphics memory to handle longer contexts. Use the Workstation Configurator to customize your system to your specific needs. Or start with our AI workstations and compare the four usage profiles. Our AI PC buying guide explains in detail which hardware you need.