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MacBook Air M5 32GB

Apple · M5 · 32GB Unified Memory · Can run 56 models

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Manufacturer Apple
Unified Mem 32 GB
Chip M5
CPU Cores 10
GPU Cores 10
Neural Engine 16
Bandwidth 120 GB/s
MSRP $1,499
Released Mar 11, 2026

AI Notes

The MacBook Air M5 32GB is the most capable Air for local AI work. With 32GB of unified memory, it fits 30B parameter models at Q4 quantization and runs 13B models at higher quality settings. Despite its fanless design, the 120 GB/s bandwidth delivers responsive inference for serious AI experimentation.

Compatible Models

Model Parameters Best Quant VRAM Used Fit Est. Speed
Qwen 3 0.6B 600M Q4_K_M 2.5 GB Runs ~48 tok/s
Gemma 3 1B 1B Q8_0 2 GB Runs ~60 tok/s
Llama 3.2 1B 1B Q8_0 3 GB Runs ~40 tok/s
DeepSeek R1 1.5B 1.5B Q8_0 3 GB Runs ~40 tok/s
Gemma 2 2B 2B Q8_0 4 GB Runs ~30 tok/s
Gemma 3n E2B 2B Q4_K_M 3.3 GB Runs ~36 tok/s
Llama 3.2 3B 3B Q8_0 5 GB Runs ~24 tok/s
Phi-3 Mini 3.8B 3.8B Q8_0 5.8 GB Runs ~21 tok/s
Phi-4 Mini 3.8B 3.8B Q4_K_M 4.5 GB Runs ~27 tok/s
Gemma 3 4B 4B Q4_K_M 5 GB Runs ~24 tok/s
Gemma 3n E4B 4B Q4_K_M 4.5 GB Runs ~27 tok/s
Qwen 3 4B 4B Q4_K_M 4.5 GB Runs ~27 tok/s
DeepSeek R1 7B 7B Q8_0 9 GB Runs ~13 tok/s
Falcon 3 7B 7B Q4_K_M 6.8 GB Runs ~18 tok/s
Mistral 7B 7B Q8_0 9 GB Runs ~13 tok/s
Qwen 2.5 7B 7B Q8_0 9 GB Runs ~13 tok/s
Qwen 2.5 Coder 7B 7B Q8_0 9 GB Runs ~13 tok/s
Qwen 2.5 VL 7B 7B Q4_K_M 7 GB Runs ~17 tok/s
Cogito 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
DeepSeek R1 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
Llama 3.1 8B 8B Q8_0 10 GB Runs ~12 tok/s
Nemotron 3 Nano 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
Qwen 3 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
Gemma 2 9B 9B Q8_0 11 GB Runs ~11 tok/s
Falcon 3 10B 10B Q4_K_M 8.5 GB Runs ~14 tok/s
Llama 3.2 Vision 11B 11B Q4_K_M 8.5 GB Runs ~14 tok/s
Gemma 3 12B 12B Q4_K_M 10.5 GB Runs ~11 tok/s
Mistral Nemo 12B 12B Q4_K_M 9.5 GB Runs ~13 tok/s
DeepSeek R1 14B 14B Q4_K_M 9.9 GB Runs ~12 tok/s
Phi-4 14B 14B Q4_K_M 9.9 GB Runs ~12 tok/s
Phi-4 Reasoning 14B 14B Q4_K_M 11 GB Runs ~11 tok/s
Qwen 2.5 14B 14B Q4_K_M 9.9 GB Runs ~12 tok/s
Qwen 2.5 Coder 14B 14B Q4_K_M 12 GB Runs ~10 tok/s
Qwen 3 14B 14B Q4_K_M 12 GB Runs ~10 tok/s
StarCoder2 15B 15B Q8_0 17 GB Runs ~7 tok/s
Codestral 22B 22B Q4_K_M 14.7 GB Runs ~8 tok/s
Devstral 24B 24B Q4_K_M 17 GB Runs ~7 tok/s
Magistral Small 24B 24B Q4_K_M 17 GB Runs ~7 tok/s
Mistral Small 3.1 24B 24B Q4_K_M 18 GB Runs ~7 tok/s
Gemma 2 27B 27B Q4_K_M 17.7 GB Runs ~7 tok/s
Gemma 3 27B 27B Q4_K_M 20 GB Runs ~6 tok/s
Qwen 3 30B-A3B (MoE) 30B Q4_K_M 22 GB Runs ~5 tok/s
Cogito 32B 32B Q4_K_M 21.5 GB Runs ~6 tok/s
DeepSeek R1 32B 32B Q4_K_M 20.7 GB Runs ~6 tok/s
Qwen 2.5 32B 32B Q4_K_M 20.7 GB Runs ~6 tok/s
Qwen 2.5 Coder 32B 32B Q4_K_M 23 GB Runs ~5 tok/s
Qwen 3 32B 32B Q4_K_M 23 GB Runs ~5 tok/s
QwQ 32B 32B Q4_K_M 21.5 GB Runs ~6 tok/s
Command R 35B 35B Q4_K_M 22.5 GB Runs ~5 tok/s
Mixtral 8x7B 47B Q4_K_M 29.7 GB Runs (tight) ~4 tok/s
Cogito 70B 70B Q4_K_M 43 GB CPU Offload ~1 tok/s
DeepSeek R1 70B 70B Q4_K_M 43.5 GB CPU Offload ~1 tok/s
Llama 3.1 70B 70B Q4_K_M 43.5 GB CPU Offload ~1 tok/s
Llama 3.3 70B 70B Q4_K_M 43.5 GB CPU Offload ~1 tok/s
Qwen 2.5 72B 72B Q4_K_M 44.7 GB CPU Offload ~1 tok/s
Qwen 2.5 VL 72B 72B Q4_K_M 41 GB CPU Offload ~1 tok/s
13 model(s) are too large for this hardware.