What Is Context Length in LLMs and How It Impacts Your VRAM (and Speed)
Learn what context length in large language models (LLMs) is, how it impacts VRAM usage and speed, and practical ways to optimize performance on local GPUs.| Hardware Corner
You’ve spent weeks picking out the parts for a powerful new computer. It has a top-tier CPU, plenty of fast storage, and maybe even a respectable graphics card. You download your first large language model (LLM), excited to run it locally, only to find the experience is agonizingly slow. The text trickles out one word […]| Hardware Corner
When choosing a local LLM, one of the first specifications to check is its context window. The context size determines how many tokens you can feed into the model at once, which directly affects practical use cases like long-form reasoning, document analysis, or multi-turn conversations. For hardware enthusiasts running quantized models on limited VRAM, knowing […]| Hardware Corner
Learn what context length in large language models (LLMs) is, how it impacts VRAM usage and speed, and practical ways to optimize performance on local GPUs.| Hardware Corner
Let’s be honest: cloud LLMs are incredibly powerful and mostly free. GPT-5, Gemini Pro, Claude Sonnet 4 – you can use them for almost unlimited queries without hitting hard limits. I personally combine Gemini and ChatGPT when one hits a rate limit, and it works perfectly. So why would you want to run models locally? […]| Hardware Corner
Running large language models locally requires smart resource management. Quantization is the key technique that makes this possible by reducing memory requirements and improving inference speed. This practical guide focuses on what you need to know for local LLM deployment, not the mathematical theory[1] behind it. For the technical mathematical details of quantization, check out […]| Hardware Corner
Large Language Models (LLMs) have rapidly emerged as powerful tools capable of understanding and generating human-like text, translating languages, writing different kinds of creative content, and answering questions in an informative way. You’ve likely interacted with them through services like ChatGPT, Claude, or Gemini. While these cloud-based services offer convenience, there’s a growing interest in […]| Hardware Corner
