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Top 5 Open-Source LLMs You Should Run Locally in 2026
Our curated list of the best open-source models for local inference this year. Compare Llama 4, Qwen 3, DeepSeek, Gemma, and Mistral — with real VRAM and quality data.
阅读更多Choosing the Right Quantization: Q4_K_M vs Q8_0 vs FP16 — A Practical Guide
Understand how quantization affects model quality, VRAM usage, and inference speed. Learn which quantization format is right for your GPU and use case, with real benchmark comparisons.
阅读更多How Much VRAM Do You Really Need? A Complete Guide for LLM Users
Demystify VRAM requirements for running local LLMs. Learn the VRAM formula, understand overhead, and find out which models fit your GPU — from 4 GB to 48 GB cards.
阅读更多How to Run LLMs on AMD GPUs: ROCm, Vulkan, and Everything You Need to Know
NVIDIA isn't the only option. Learn how to run open-source LLMs on AMD Radeon GPUs using ROCm, llama.cpp with Vulkan, and other backends — with step-by-step setup instructions.
阅读更多Context Length Explained: Why 128K Tokens Matters and How It Affects VRAM
Long context windows are the defining feature of modern LLMs. Learn what context length actually means, how it impacts VRAM, and when you actually need 128K tokens.
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