Running large language models locally requires prohibitive GPU memory that most developers don't have access to

Developers and AI researchers want to run state-of-the-art large language models (like Qwen 27B) on their own hardware for privacy, cost, and latency reasons, but the 13GB+ VRAM requirements exceed what most consumer and even professional GPUs can handle. Current solutions force them to either pay for expensive cloud API access, use smaller inferior models, or invest thousands in enterprise GPU hardware they can't justify for experimentation.