Local LLM

Why It Matters

Local LLMs give you control that cloud APIs cannot. No usage limits, no per-token costs, no data sent to third parties, no internet required. For privacy-sensitive applications, regulated industries, or high-volume use cases, local deployment may be the only viable option.

The quality gap between local and cloud models is narrowing rapidly. Open-source models like Llama 3, Mistral, and Phi now rival proprietary models for many tasks. Quantization techniques let 70B parameter models run on consumer hardware. What required enterprise GPUs in 2023 runs on gaming laptops in 2025.

For AI engineers, local LLMs enable unrestricted experimentation. You can test thousands of prompts without API costs, fine-tune on proprietary data, and build applications that work completely offline. This freedom accelerates learning and prototyping.

Implementation Basics

Hardware requirements:

• CPU-only: Works but slow (1-5 tokens/second for 7B models)
• Consumer GPU (8GB+ VRAM): Reasonable speed for 7B quantized models
• Prosumer GPU (16-24GB VRAM): Comfortable for 13B-34B quantized models
• Multi-GPU or 48GB+: Required for 70B+ models without heavy quantization

Local LLM software:

• Ollama: Simplest setup, one-command model downloads, macOS/Linux/Windows
• LM Studio: GUI application, good for beginners, model browsing
• llama.cpp: Low-level, maximum performance, requires compilation
• vLLM: Production-grade serving with high throughput
• text-generation-webui: Feature-rich web interface

Model selection:

• 7B models: Fast, run on most GPUs, good for simple tasks
• 13B-34B models: Better quality, need 16GB+ VRAM quantized
• 70B models: Near cloud quality, need 48GB+ or aggressive quantization
• Task-specific: Code models (CodeLlama), instruct-tuned (Llama-chat)

Optimization techniques:

• Quantization: Q4_K_M offers good quality/size tradeoff
• Context length: Longer contexts require more VRAM
• Batch size: Larger batches improve throughput if VRAM allows
• Metal/CUDA acceleration: Essential for usable speeds

Start with Ollama for the simplest experience since ollama run llama3 gets you running immediately. Progress to more complex setups when you need specific optimizations or production serving capabilities.