Easiest Deployment Tools

For true ease of use, you’ll want to start with one of these applications. They package the models and provide a simple interface (either graphical or a single command) to get you started in minutes, with no coding required.

• Ollama: This is arguably the easiest and most popular command-line tool. It bundles model weights, configuration, and a server into one simple package. You install Ollama, then run a single command like ollama run llama3 in your terminal to download the model and start chatting. It’s available for Windows, macOS, and Linux.
• LM Studio: A fantastic desktop application with a graphical user interface (GUI). It allows you to browse and download a massive library of models (in the popular GGUF format), configure settings, and chat with the model, all within a user-friendly window. It’s perfect if you prefer not to use the command line.
• GPT4All: Another great GUI-based option that is optimized to run a wide variety of quantized models on your computer’s CPU, making it accessible even without a powerful graphics card.

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Top Open-Source LLMs for Personal Use

These models are great because they offer a fantastic balance of performance and manageable size, making them ideal for running on consumer hardware like modern laptops and desktops.

General Purpose & Chat

1. Meta Llama 3
   • Why it’s great: This is the current state-of-the-art open-source model. It’s incredibly capable for chatting, writing, summarizing, and coding.
   • Best Version for Personal Use: Llama 3 8B Instruct. The “8B” stands for 8 billion parameters. It’s the sweet spot, requiring about 8 GB of RAM/VRAM to run smoothly.
   • Supported by: Ollama, LM Studio, GPT4All.
2. Mistral 7B
   • Why it’s great: Before Llama 3, this model was the king of its size class. It’s known for being very fast, coherent, and excellent at following instructions and coding, often outperforming larger models.
   • Best Version for Personal Use: Mistral 7B Instruct. It’s very lightweight and efficient.
   • Supported by: Ollama, LM Studio, GPT4All.
3. Google Gemma
   • Why it’s great: Developed by Google, these models are built with the same technology as the powerful Gemini models. They are solid all-rounders.
   • Best Version for Personal Use: Gemma 7B for powerful machines, or Gemma 2B for less powerful ones (like laptops without a dedicated GPU).
   • Supported by: Ollama, LM Studio.

Specialized & Lightweight Models

4. Microsoft Phi-3
   • Why it’s great: A new generation of “small language models” (SLMs) that pack a surprising punch. They are designed to run very efficiently on low-resource devices, including phones.
   • Best Version for Personal Use: Phi-3 Mini 3.8B. It performs at a level far above what you’d expect from such a small model, making it perfect for laptops or older desktops.
   • Supported by: Ollama, LM Studio.
5. Qwen2 (from Alibaba Cloud)
   • Why it’s great: A very strong family of models with excellent multilingual capabilities and strong performance in both chat and coding. They come in many sizes.
   • Best Version for Personal Use: Qwen2 7B is a great Llama 3 alternative. For lower-spec machines, Qwen2 1.5B is a fantastic and fast option.
   • Supported by: Ollama, LM Studio.

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What You Need to Consider

• VRAM (GPU Memory): This is the most important factor. The model needs to be loaded into your graphics card’s memory. A model’s size (e.g., 7B) roughly corresponds to the VRAM needed in GB (e.g., a 7B model needs about 7-8 GB of VRAM).
• Quantization: This is a technique to shrink models to run on less powerful hardware, with a small trade-off in performance. Tools like LM Studio and Ollama handle this for you automatically, downloading pre-quantized versions so you don’t have to worry about it.
• CPU vs. GPU: While you can run these models on your CPU, it will be much slower. For a good interactive experience, a modern dedicated GPU (like an NVIDIA RTX 3060 or better) with at least 8 GB of VRAM is recommended.