Faster hardware unlocks smarter, larger LLMs

Faster hardware acts as the intelligence bandwidth for local AI, where increased VRAM and compute translate directly to superior reasoning and reduced compression artifacts. High VRAM capacity enables the use of 70B+ parameter models, while better bandwidth supports higher precision quantizations that preserve model intelligence. Additionally, faster inference makes compute-heavy strategies like Chain-of-Thought and multi-pass agentic workflows practical for real-world applications.