text model · gemma · macOS

Can I run Gemma 2 27B on Apple M4 Pro (24GB)?

Compatibility verdict VRAM threshold engine

No, not enough memorywould not load

No. Gemma 2 27B needs ~18.7 GB even at Q4_K_M, but Apple M4 Pro (24GB) only has ~16 GB usable.

usable ~16 GB

Needs ~18.7 GB Device usable ~16 GB

Needs ~18.7 GB even at Q4_K_M, but only ~16 GB is usable.

Q4_K_M needed: ~18.7 GB
Usable on device: ~16 GB
Device memory: 24 GB

Model gemma

Parameters: 27B
Q4_K_M size: 16.65 GB
Q8_0 size: 28.94 GB
Context: 8k
Ollama tag: gemma2:27b

Full Gemma 2 27B requirements →

Device macOS

Memory: 24 GB unified
Usable for weights: ~16 GB
Best runtime: Ollama (MLX backend, preview) / MLX direct

Best models for Apple M4 Pro (24GB) →

What you can run instead

Run Gemma 2 27B on other hardware

Nvidia GeForce RTX 4090 (24GB)Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)32GB RAM Laptop (CPU/iGPU only)Apple M5 (32GB)

FAQ

Can Apple M4 Pro (24GB) run Gemma 2 27B?

No. Gemma 2 27B needs ~18.7 GB even at Q4_K_M, but Apple M4 Pro (24GB) only has ~16 GB usable.

How much memory does Gemma 2 27B need?

Apple M4 Pro (24GB) does not have enough memory. At Q4_K_M the weights are ~16.65 GB; with KV cache and runtime overhead, budget ~18.7 GB at a 4k context.

What is the best tool to run Gemma 2 27B on macOS?

LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

Sources

Memory figures are estimates. See methodology.