text model · Gemma · macOS

Can I run Gemma 4 26B-A4B on Apple M2 (16GB)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Gemma 4 26B-A4B needs ~19 GB even at Q4_K_M, but Apple M2 (16GB) only has ~10.5 GB usable.

Needs ~19 GB Device usable ~10.5 GB

Needs ~19 GB even at Q4_K_M, but only ~10.5 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 8.5 GB: Gemma 4 26B-A4B needs roughly 19 GB at Q4_K_M and Apple M2 (16GB) leaves only about 10.5 GB usable for a model. The lightest tracked hardware that runs Gemma 4 26B-A4B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Gemma 4 26B-A4B on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed: ~19 GB
Usable on device: ~10.5 GB
Device memory: 16 GB

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Which quant fits

Quant ladder vs ~10.5 GB usable

Q2_K

~13.1 GB

Q3_K_M

~15 GB

Q4_K_M

~19 GB

Q5_K_M

~20.9 GB

Q6_K

~23.7 GB

Q8_0

~28.9 GB

FP16

~52.5 GB

The line marks Apple M2 (16GB)'s ~10.5 GB budget; rungs past it are too large.

Model Gemma

Parameters: 26.5B (MoE, 3.8B active)
Q4_K_M size: 17.04 GB
Q8_0 size: 26.86 GB
Context: 256k
Ollama tag: gemma4:26b-a4b

Full Gemma 4 26B-A4B requirements →

Device macOS

Memory: 16 GB unified
Usable for weights: ~10.5 GB
Power draw: ~50 W
Best runtime: Ollama (llama.cpp Metal backend) / MLX

Best models for Apple M2 (16GB) →

What you can run instead

Run Gemma 4 26B-A4B 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 M2 (16GB) run Gemma 4 26B-A4B?

No. Gemma 4 26B-A4B needs ~19 GB even at Q4_K_M, but Apple M2 (16GB) only has ~10.5 GB usable.

How much memory does Gemma 4 26B-A4B need?

Apple M2 (16GB) does not have enough memory. At Q4_K_M the weights are ~17.04 GB; with KV cache and runtime overhead, budget ~19 GB at a 4k context. It is a Mixture-of-Experts model (26.5B total / 3.8B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Gemma 4 26B-A4B 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.

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Markdown

[![Gemma 4 26B-A4B on Apple M2 (16GB)](https://localmodel.run/badge/gemma-4-26b-a4b/apple-m2-16gb.svg)](https://localmodel.run/can-i-run/gemma-4-26b-a4b/apple-m2-16gb)

Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.