text model · Granite · macOS

Can I run Granite 4.0 H Small on Apple M3 Pro (18GB)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Granite 4.0 H Small needs ~20.3 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.

Needs ~20.3 GB Device usable ~12 GB

Needs ~20.3 GB even at Q4_K_M, but only ~12 GB is usable.

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

The gap is about 8.3 GB: Granite 4.0 H Small needs roughly 20.3 GB at Q4_K_M and Apple M3 Pro (18GB) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Granite 4.0 H Small is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Granite 4.0 H Small on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed: ~20.3 GB
Usable on device: ~12 GB
Device memory: 18 GB

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Which quant fits

Quant ladder vs ~12 GB usable

Q2_K

~15.6 GB

Q3_K_M

~17.8 GB

Q4_K_M

~20.3 GB

Q5_K_M

~25 GB

Q6_K

~28.4 GB

Q8_0

~34.1 GB

FP16

~66.6 GB

The line marks Apple M3 Pro (18GB)'s ~12 GB budget; rungs past it are too large.

Model Granite

Parameters: 32B (MoE, 9B active)
Q4_K_M size: 18.14 GB
Q8_0 size: 31.91 GB
Context: 128k
Ollama tag: granite4:32b-a9b-h

Full Granite 4.0 H Small requirements →

Device macOS

Memory: 18 GB unified
Usable for weights: ~12 GB
Power draw: ~70 W
Best runtime: Ollama (llama.cpp Metal backend) / MLX

Best models for Apple M3 Pro (18GB) →

What you can run instead

Run Granite 4.0 H Small 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 M3 Pro (18GB) run Granite 4.0 H Small?

No. Granite 4.0 H Small needs ~20.3 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.

How much memory does Granite 4.0 H Small need?

Apple M3 Pro (18GB) does not have enough memory. At Q4_K_M the weights are ~18.14 GB; with KV cache and runtime overhead, budget ~20.3 GB at a 4k context. It is a Mixture-of-Experts model (32B total / 9B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Granite 4.0 H Small 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

[![Granite 4.0 H Small on Apple M3 Pro (18GB)](https://localmodel.run/badge/granite-4-h-small/apple-m3-18gb.svg)](https://localmodel.run/can-i-run/granite-4-h-small/apple-m3-18gb)

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.