Thanks to advancements in quantization and GPU alternatives, running local LLMs is mainstream in 2025.
Why companies choose private LLMs
- Regulatory compliance.
- Data confidentiality.
- Lower long-term inference cost.
Typical stack
- Llama 3‑70B Q4 or Mistral Large.
- Kubernetes + vector DB.
- Hardware: A100/H100 or AMD MI300.
Example architecture
User → API Gateway → LLM Inference → Vector Store → Logging → Audit Layer.
Summary
On‑prem LLMs are no longer experimental—they are a primary choice for regulated industries in 2025.