Local AI Model Guide

Meta's flagship instruction-tuned model — the current standard for high-quality local AI on consumer hardware.

Alibaba's 72B model with exceptional instruction following and multilingual capability — frequently outperforms Llama 3.3 70B on structured tasks.

Meta's next-generation mixture-of-experts model — frontier-class capability at MoE efficiency, requiring 64GB+ RAM.

DeepSeek's reasoning-focused model trained with reinforcement learning — exceptional at math, logic, and structured thinking.

The sweet spot for 24GB RAM configurations — excellent quality without the memory demands of 70B models.

Alibaba's dedicated coding model at 32B parameters — tops most coding benchmarks for its size class across 92+ languages.

The smaller variant of DeepSeek's reasoning model — excellent for math, logic, and structured analysis on 24GB hardware.

Google's open-source 27B model with multimodal capability — vision plus text in a single 24GB-compatible package.

Mistral AI's efficient 24B model — strong instruction following and business task performance with a low memory footprint.

An 80B mixture-of-experts coding model designed for large codebase analysis, complex refactoring, and architectural reasoning.

Microsoft's research model optimized for STEM and reasoning — punches well above its 14B weight on math and logic.

Qwen's efficient 14B model — solid general-purpose chat and instruction following, good balance of speed and capability for 16GB configs.

Google's efficient 12B model with good multilingual support and capable everyday performance.

Co-developed by Mistral and NVIDIA — efficient 12B model with solid chat and basic coding capability.

Qwen's fast 8B model — excellent for quick queries and automation tasks where speed matters more than maximum quality.

Meta's entry-level instruction model — reliable for basic tasks, fast on any Apple Silicon Mac with 8GB+ RAM.

Google's compact 4B model — ultra-fast responses on any Apple Silicon, best for automation triggers and speed-critical tasks.

Meta's smallest capable model — runs on any Mac, responds in milliseconds, used primarily for automation and routing.