VRAM Needed to Run Local LLMs: 7B to 70B Guide

Wed, 16 Sep 2026 02:26:30 +0000

To run a local large language model (LLM) comfortably on your own hardware, you need between 6 GB of VRAM for an entry-level 7B or 8B model up to 48 GB of VRAM for a flagship 70B model at standard 4-bit quantization. Memory capacity is the single most critical bottleneck in local AI: if a model exceeds your dedicated video memory, inference either crashes with an Out of Memory (OOM) error or offloads partially to system RAM, causing generation speed to collapse by 80% to 95%.

Running Local AI Models: Why It Is Finally Good Now

Wed, 17 Jun 2026 06:57:49 +0000

For the past two years, the artificial intelligence revolution has been inextricably tied to the cloud. When ChatGPT first exploded onto the scene, the underlying assumption was that interacting with a state-of-the-art language model required massive server farms, thousands of expensive GPUs, and a high-speed internet connection. Consumers and developers alike accepted the reality of monthly subscriptions, usage caps, and the nagging concern of handing over personal or corporate data to distant servers.

Local Llm on NV Trends

VRAM Needed to Run Local LLMs: 7B to 70B Guide

Running Local AI Models: Why It Is Finally Good Now