Blog hub

Local LLM Blog

Practical guides around what users actually search for: what fits in your VRAM, how to choose models on Mac, how quantization works, which coding and vision models to run locally.

Video Memory Guide

What local large models can be run with different graphics memories?

From 6GB, 8GB, 12GB, 24GB to 48GB, explain how model parameter volume, quantized version, KV cache and system overhead combine to determine whether it can be loaded.

Apple chip

How does Apple Unified Memory affect local LLM?

Explain why the total memory on Mac cannot be used as video memory, and how to choose the suitable model for 16GB, 32GB, 64GB, and 128GB machines.

Quantify

Q4, Q5, Q6, Q8 How should I choose quantification?

The more common GGUF quantification of memory usage, quality loss and speed trade-off helps users understand the three preferences of quality priority, balance and long context.

programming model

How to choose a local LLM suitable for programming?

From the four scenarios of code generation, interpretation, reconstruction and long context, explain why programming purposes cannot just look at model size and download volume.

multimodal

How to run local vision model and multi-modal model?

This article introduces the additional issues of graphics memory, image encoder, context, and reasoning back-end support that need to be considered in visual models compared to text models.

Tool selection

What are the differences between Ollama, LM Studio, and llama.cpp?

Explain to ordinary users the installation experience, model management, performance tuning and applicable groups of three common local running methods.

VRAM Guide

Is 6GB VRAM Enough for a Local LLM?

A practical guide to what 6GB graphics cards can run locally, which model sizes and quantization levels make sense, and when upgrading is the better answer.

Hardware Guide

Best GPU for Local LLMs: What Actually Matters

How to choose a GPU for local LLM inference by VRAM, memory bandwidth, software support, quantization needs, and the size of models you want to run.

Model Selection

What Local LLM Can I Run? A Practical Selection Guide

A step-by-step guide to matching your RAM, VRAM, operating system, use case, and quality preference to local models that are actually runnable.

Model guide

Local LLM Models Explained: Sizes, Formats, and Tradeoffs

A practical guide to local LLM model families, parameter counts, GGUF files, quantization levels, context length, and how to choose a model that fits your hardware.

Hardware guide

How Much VRAM Do You Need for a Local LLM?

A hardware-first guide to VRAM requirements for local LLMs, including model weights, quantization, KV cache, context length, runtime overhead, and realistic GPU tiers.

Windows guide

Run an LLM Locally on Windows: Hardware, Tools, and Setup

A practical Windows guide for running local LLMs with Ollama, LM Studio, llama.cpp, GPU drivers, model selection, VRAM planning, and common troubleshooting steps.

macOS guide

Run an LLM Locally on macOS: Apple Silicon, Memory, and Tools

A practical macOS guide for running local LLMs on Apple Silicon, covering unified memory, MLX, Metal, Ollama, LM Studio, llama.cpp, model choice, and realistic limits.

Linux guide

Run an LLM Locally on Linux: GPUs, Drivers, Tools, and Setup

A practical Linux guide for running local LLMs with NVIDIA CUDA, AMD ROCm, Ollama, LM Studio, llama.cpp, model formats, VRAM planning, and server safety.

Model guide

Best Local AI Models: How to Choose What Runs on Your Hardware

A practical guide to choosing the best local AI models for chat, coding, writing, math, vision, and offline use based on hardware fit, quantization, benchmarks, and model format.

Model guide

Best Local LLM Models: How to Pick the Right One

A practical guide to choosing the best local LLM models for your hardware, including model size, quantization, GGUF files, coding, writing, reasoning, vision, and memory fit.

Model guide

Best LLM to Run Locally: A Practical Hardware-First Guide

A practical guide to finding the best LLM to run locally on your computer, based on VRAM, RAM, operating system, model size, quantization, speed, privacy, and use case.

Comparison guide

Local LLM vs Cloud LLM: Which Should You Use?

A practical comparison of local LLMs and cloud LLMs across privacy, cost, speed, quality, hardware, offline use, maintenance, and real-world workflows.

Model guide

Local AI Model Guide: How to Choose What Runs on Your Computer

A practical guide to local AI models, covering LLMs, vision models, embeddings, hardware fit, quantization, privacy, tools, and download choices.

Offline AI

Offline AI: What Can Run Locally Without the Cloud?

A practical guide to what offline AI can do locally, including chat, coding, writing, summarization, embeddings, vision, hardware limits, and privacy tradeoffs.

Beginner guide

Local LLM for Beginners: Hardware, Models, and First Steps

A beginner-friendly guide to local LLMs, explaining hardware, VRAM, RAM, quantization, model files, tools, privacy, and how to choose a first model.

Setup guide

Local LLM Setup Checklist: Hardware, Models, Tools, and Safety

A practical setup checklist for running a local LLM, covering hardware, VRAM, RAM, model choice, quantization, tools, local servers, testing, and safety.

FAQ

Local LLM FAQ: Answers Before You Download a Model

Clear answers to common local LLM questions about VRAM, RAM, GPU choice, quantization, privacy, speed, offline use, tools, and model downloads.

Tool guide

Cursor with Local LLM: What Works, What Breaks, and How to Choose a Model

A practical guide to using Cursor with a local LLM, covering Ollama, LM Studio, OpenAI-compatible endpoints, coding models, hardware limits, speed, privacy, and setup checks.

Tool guide

How to Use Local Models with Cursor.ai: Setup, Limits, and Model Choice

A practical Cursor.ai local model guide covering OpenAI-compatible endpoints, Ollama, LM Studio, coding models, hardware limits, privacy, speed, and troubleshooting.

Model selection

Best Local LLM for Cursor: How to Choose a Coding Model That Actually Helps

A hardware-first guide to choosing the best local LLM for Cursor, covering coding quality, context, speed, quantization, VRAM, privacy, and practical testing.

Tool guide

LM Studio Local LLM Guide: Models, Server Setup, Hardware, and Safety

A practical LM Studio local LLM guide covering model downloads, GGUF and MLX choices, OpenAI-compatible server setup, hardware fit, privacy, and testing.