AI model recommendations for MacBook Pro M4 with up to 128GB RAM. Fastest inference for all model sizes. This configuration provides optimal performance for local AI models.
The M4 MacBook Pro delivers the fastest AI inference in the laptop lineup. Enhanced Neural Engine and improved memory bandwidth make it the best choice for professionals running large models daily.
Based on our analysis, 8 out of 8 recommended models run excellently on this configuration. The sweet spot for MacBook Pro with Apple M4 is 14B-70B parameter models with Q4_K_M quantization, which provides the best trade-off between quality and inference speed.
Qwen / 9B / Q4_K_M / ~7 GB
Best for: Quality, Coding, Reasoning·Pop: 86/100
Perf: ~59.6 tok/s · first token ~0.6s
Best for quality, coding, reasoning. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run qwen3.5:9b-instruct-q4_K_M
LFM2 / 24B / Q4_K_M / ~14 GB
Best for: Local AI agents, privacy-first tool calling, MCP workflows·Pop: 80/100
Perf: ~24.7 tok/s · first token ~0.9s
Best for local ai agents, privacy-first tool calling, mcp workflows. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run liquidai/lfm2:24b-a2b-instruct-q4_K_M
Gemma / 9B / Q4_K_M / ~7 GB
Best for: Chat, Coding·Pop: 81/100
Perf: ~59.6 tok/s · first token ~0.6s
Best for chat, coding. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run gemma2:9b-instruct-q4_K_M
Qwen / 14B / Q4_K_M / ~11 GB
Best for: Coding, Quality·Pop: 84/100
Perf: ~40.1 tok/s · first token ~0.7s
Best for coding, quality. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run qwen3:14b-q4_K_M
Qwen / 14B / Q4_K_M / ~11 GB
Best for: Coding·Pop: 79/100
Perf: ~40.1 tok/s · first token ~0.7s
Best for coding. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run qwen2.5-coder:14b-q4_K_M
Qwen / 14B / Q4_K_M / ~11 GB
Best for: Coding, Chat·Pop: 80/100
Perf: ~40.1 tok/s · first token ~0.7s
Best for coding, chat. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run qwen2.5:14b-instruct-q4_K_M
Mistral / 12B / Q4_K_M / ~9.5 GB
Best for: Chat, Translation·Pop: 78/100
Perf: ~46.0 tok/s · first token ~0.7s
Best for chat, translation. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run mistral-nemo:12b-q4_K_M
Gemma / 12B / Q4_K_M / ~9.5 GB
Best for: Chat, Quality·Pop: 76/100
Perf: ~46.0 tok/s · first token ~0.7s
Best for chat, quality. Strong fit for 32 GB RAM with balanced speed and quality.
ollama run gemma3:12b-instruct-q4_K_M
With 32GB RAM and the Apple M4 chip, we recommend Qwen3.5 9B Instruct for the best balance of speed and quality. The Apple M4 handles 14B-70B parameter models well.
MacBook Pro with Apple M4 supports 16, 32GB configurations. For most AI workloads, 32GB provides good headroom. A 7B model typically needs 4-5GB of free RAM, while 14B models need 8-10GB.
Apple M4 on MacBook Pro achieves approximately 59.6 tokens per second with optimized models. The M4 MacBook Pro delivers the fastest AI inference in the laptop lineup. Enhanced Neural Engine and improved memory bandwidth make it the best choice for professionals running large models daily.
Yes, Ollama runs natively on Apple Silicon including Apple M4. You can install it in minutes and run models like Qwen3.5 9B Instruct locally. Our wizard recommends the best models based on your exact Apple M4 configuration and available RAM.
Use our interactive wizard to test different RAM configurations and priorities for your specific Apple M4 setup.
Open ModelFit Wizard →