Run AI Locally
on Your Mac

Yes. Every Apple Silicon Mac (M1 and newer) can run local AI models. Unified memory means even an 8 GB MacBook Air can run compact models such as Gemma 4 E4B (multimodal with audio), Qwen 3 4B or Phi-4 Mini, and more memory lets you run larger models such as Gemma 4 26B-A4B or Qwen 3.6-35B-A3B on a 24 GB Mac.

It depends on your unified memory. As of 24 October 2026, Qwen 3.6-35B-A3B ranks #1 (LLMCheck Score 81) at 118 tok/s published on an M5 Max and runs on a Mac with at least 24 GB of unified memory, so it is also the best pick for a Mac with 32 GB or less. Best pick for each RAM tier (llmcheck.net/best-llm/by-ram/): 8 GB: Nanbeige4.2-3B; 16 GB: Gemma 4 12B; 24 GB: Qwen 3.6-35B-A3B; 32 GB: Qwen 3.6-35B-A3B; 64 GB: LFM2.5-24B-A2B; 128 GB: Qwen3.8-Flash-Next; 192–256 GB: MiMo-V2.6-Flash; 512 GB: MiMo-V2.6-Flash. The strongest dense model is Qwen3.8-27B. Use the checker above for a recommendation matched to your exact Mac.

For beginners, apps such as LM Studio or Jan give you a chat window: download, pick a model and start chatting, with no terminal or coding. For more control, Ollama runs in the background and, since version 0.40, runs supported models on Apple's MLX by default on Apple Silicon. Developers may prefer llama.cpp or Apple's MLX directly.

Yes, completely free. All the models and software listed here are open-source or free to use. There are no subscriptions, no per-message fees and no usage limits. The only cost is the Mac hardware you already own.

According to the LLMCheck index, a model needs about 0.57 GB per billion parameters at 4-bit (Q4_K_M) plus about 2 GB for the KV cache and runtime, so an 8B model needs about 7 GB and a 27B dense model about 18 GB. A mixture-of-experts model must hold all of its parameters, not just the active ones. As a guide: 8 GB runs 3-8B models; 16 GB runs 12-14B models and GPT-oss 20B; 24-32 GB runs 27-35B models such as Qwen3.8-27B and Qwen 3.6-35B-A3B; 64 GB runs 70B dense models and GPT-oss 120B; 128 GB runs 120-230B mixture-of-experts models at 2-4 bits; 256-512 GB Mac Studios run 300B to 1T models at 2-4 bits. macOS lets the GPU use about 75% of unified memory by default.

Yes, but with limitations. Intel Macs lack the Neural Engine and unified memory of Apple Silicon, so models run on the CPU only, which is significantly slower. Compact models (1-3B parameters) are still usable. For the best experience, Apple Silicon (M1 or later) is strongly recommended.