Unlocking GPU Acceleration for Ollama: A Docker-Based Solution to Local LLM Performance

GPU utilization is critical for practical local LLM deployment, and this guide solves a common bottleneck where Ollama defaults to CPU inference despite available NVIDIA hardware. For developers running language models on personal machines, this Docker-based approach eliminates environment-specific GPU configuration challenges and delivers dramatic performance improvements. The solution demonstrates how containerization can simplify hardware integration, making efficient local AI development accessible to a broader audience.