Meta's Llama 4 Scout, a 109 billion parameter mixture-of-experts model, requires approximately 25GB of VRAM for usable performance at Q4_K_M quantization. The RTX 5090 with 32GB of VRAM is presented as the sole single consumer GPU capable of running the model locally. For a more cost-effective local solution, a dual RTX 3090 setup offers comparable performance and more VRAM for a similar price, though it involves greater complexity. Cloud GPU instances are recommended for users who only need to run the model occasionally. AI
Summary written by gemini-2.5-flash-lite from 1 sources. How we write summaries →
IMPACT Provides crucial hardware guidance for running advanced LLMs locally, impacting AI operators and researchers.
RANK_REASON Article details hardware requirements and performance benchmarks for a specific LLM, akin to a technical deep-dive or research paper analysis. [lever_c_demoted from research: ic=1 ai=1.0]