text model · Gemma · macOS

Can I run Gemma 4 26B-A4B on Apple M5 Pro (48GB)?

Compatibility verdict VRAM threshold engine

Yes, it runs GPU accelerated

Yes. Gemma 4 26B-A4B runs on Apple M5 Pro (48GB) at Q4_K_M (~19 GB of ~32 GB usable).

Needs ~19 GB Device usable ~32 GB

Runs at Q4_K_M using ~19 GB of ~32 GB usable. You have room for Q8_0 for higher quality.

That figure is at a 4k context and moves about ±15% as context length changes. Apple M5 Pro (48GB) leaves ~13 GB of headroom, room to step up to Q8_0 for higher quality.

Q4_K_M needed: ~19 GB
Usable on device: ~32 GB
Device memory: 48 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~32 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 M5 Pro (48GB)'s ~32 GB budget; rungs past it are too large.

Run it

Install commands macOS

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama

$ ollama run gemma4:26b-a4b

llama.cpp

$ llama-cli -hf bartowski/google_gemma-4-26B-A4B-it-GGUF:Q4_K_M

LM Studio

$ lms get bartowski/google_gemma-4-26B-A4B-it-GGUF

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: 48 GB unified
Usable for weights: ~32 GB
Best runtime: MLX direct / Ollama (MLX backend)

Best models for Apple M5 Pro (48GB) →

You could also run

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 M5 Pro (48GB) run Gemma 4 26B-A4B?

Yes. Gemma 4 26B-A4B runs on Apple M5 Pro (48GB) at Q4_K_M (~19 GB of ~32 GB usable).

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

Apple M5 Pro (48GB) has room to spare. 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 M5 Pro (48GB)](https://localmodel.run/badge/gemma-4-26b-a4b/apple-m5-pro-48gb.svg)](https://localmodel.run/can-i-run/gemma-4-26b-a4b/apple-m5-pro-48gb)

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.