Best Local AI Models for Apple Silicon in 2026

Apple Silicon has fundamentally changed what's possible with local AI. The unified memory architecture of M-series chips means you can run models that previously required expensive NVIDIA GPUs — right on your MacBook.

But with thousands of models available, which ones actually perform best on Apple Silicon? We've tested dozens of models across different sizes and use cases. Here are our top picks for 2026.

Best Overall: Qwen 3.5

Alibaba's Qwen 3.5 family has become the go-to choice for local AI on Mac. Available in sizes from 0.5B to 72B parameters, Qwen 3.5 models deliver exceptional performance across the board:

• Qwen 3.5 2B — Perfect for 8GB Macs. Fast inference, surprisingly capable for its size.
• Qwen 3.5 4B — The sweet spot for 16GB Macs. Great reasoning and coding.
• Qwen 3.5 9B — Excellent quality-to-size ratio. Runs well on 16GB with quantization.

Qwen 3.5 also features strong multilingual support, making it ideal if you work in languages beyond English.

Best for Coding: DeepSeek Coder V2

If coding assistance is your primary use case, DeepSeek models are hard to beat. DeepSeek's specialized coding models understand complex codebases and generate high-quality code across dozens of programming languages.

• DeepSeek Coder 1.5B — Lightweight coding assistant for quick tasks
• DeepSeek Coder 7B — Full-featured coding companion that runs on 16GB Macs
• DeepSeek R1 — Advanced reasoning model for complex problem-solving

Best for Low RAM: Phi-3

Microsoft's Phi-3 family proves that small models can punch well above their weight. If you have an 8GB Mac, Phi-3 is your best friend:

• Phi-3 Mini (3.8B) — Runs comfortably on 8GB RAM with room to spare
• Phi-3 Medium (14B) — Excellent quality for 16GB Macs

Phi-3 models are particularly impressive for instruction-following tasks and general Q&A. Their efficiency makes them ideal for always-on AI assistants.

Best Open-Source Flagship: Llama 3.1

Meta's Llama 3.1 remains the benchmark for open-source AI. It set the standard that other models are measured against:

• Llama 3.1 8B — The workhorse. Great all-round performance on 16GB Macs.
• Llama 3.2 3B — Optimized for mobile and edge. Fast on any Apple Silicon Mac.
• Llama 3.1 70B — Flagship quality for 64GB+ Macs. Competes with closed-source models.

Best for Speed: Gemma 2

Google's Gemma 2 models are optimized for inference speed. If low latency is your priority — for example, real-time chat or interactive applications — Gemma is an excellent choice:

• Gemma 2 2B — Blazing fast. Great for quick questions and simple tasks.
• Gemma 2 9B — Good balance of speed and capability.
• Gemma 2 27B — High quality with competitive speed on 32GB Macs.

Best for Creative Writing: Mistral

Mistral models have earned a reputation for creative, nuanced writing. If you need AI for storytelling, content creation, or brainstorming, Mistral's models tend to produce more engaging and varied outputs:

• Mistral 7B — Surprisingly creative for a 7B model
• Mixtral 8x7B — Mixture-of-experts architecture for diverse, high-quality outputs (needs 32GB+)

MLX vs GGUF: Which Format to Choose?

On Apple Silicon, you have two format options:

• MLX — Always prefer this when available. It's built for Apple Silicon's unified memory and delivers the best performance.
• GGUF — Use when a model isn't available in MLX format. The broader compatibility means more model options.

In our testing, MLX models consistently deliver 20-40% faster token generation compared to equivalent GGUF models on the same hardware.

Our Recommendations by Mac

• MacBook Air 8GB — Qwen 3.5 1.7B (MLX) or Phi-3 Mini 3.8B (Q4)
• MacBook Pro 16GB — Qwen 3.5 8B (MLX) or Llama 3.1 8B (MLX)
• MacBook Pro 32GB — Qwen 3.5 32B (Q4) or DeepSeek R1 16B
• Mac Studio 64GB+ — Llama 3.1 70B (Q4) or Qwen 3.5 72B (Q4)

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All of these models are available in Lekh AI. Browse, download, and start chatting — all within the app. No terminal commands, no configuration files, no hassle.