Can Granite 4.2 30B run on MacBook Pro M3 Pro 18GB?
What this means
Granite 4.2 30B fits on the MacBook Pro M3 Pro · 18GB at Q2_K. We estimate it uses 14.3GB of the conservative 15GB working budget.
Estimated decode speed is 6.9–9.6 tokens/s. A roughly 300-word answer may take around 48 seconds.
See how fast it feels
Using the midpoint of our 6.9–9.6 tokens/s estimate for this demo.
Where the memory goes
| Component | Detail | GB |
|---|---|---|
| Model weights | Q2_K GGUF (10.9 GB) + mmap overhead | 11.4 |
| KV cache | 4K context window | 2.1 |
| Runtime | macOS inference app + compute buffers | 0.8 |
| Total needed | at Q2_K, 4K context | 14.3 |
| Working budget | 18 GB unified memory − conservative macOS reserve | 15 |
| Headroom | remaining inside the working budget | 0.7 |
Pick your quant
| Quant | Download | Memory | Estimated speed | Verdict |
|---|---|---|---|---|
| Q2_K ★ | 10.9 GB | 14.3 GB | ~6.9–9.6 tok/s | ! Runs, barely |
| Q3_K_M | 14.1 GB | 17.7 GB | — | ✕ Won't fit |
| Q4_0 | 16.6 GB | 20.3 GB | — | ✕ Won't fit |
| Q4_K_S | 16.7 GB | 20.4 GB | — | ✕ Won't fit |
| Q4_K_M | 17.7 GB | 21.5 GB | — | ✕ Won't fit |
| Q5_K_M | 20.8 GB | 24.7 GB | — | ✕ Won't fit |
| Q6_K | 24 GB | 28.1 GB | — | ✕ Won't fit |
| Q8_0 | 31.1 GB | 35.6 GB | — | ✕ Won't fit |
Get it running on this Mac
Recommended app: LM Studio. Follow the point-and-click steps below.
Download LM Studio from its official site and drag it to Applications. Open it once and allow macOS to launch it. This route uses the graphical app; you do not need its CLI or local-server features.
Search for ibm-granite/granite-4.2-30b-GGUF. Use the publisher name shown on this page—or paste its full Hugging Face URL. Similarly named community uploads may contain different files.
Open the GGUF download options and select the row containing Q2_K. The download should be about 10.9 GB. Do not select vision-projector or mmproj helper files for a text-only chat.
Choose the downloaded model in the model selector and click Load if prompted. Keep the default local runtime and start with a 4K (4096-token) context. Close memory-heavy apps for the first load.
Try “Explain why the sky is blue in three sentences.” This page estimates 6.9–9.6 tokens/s; it is not an LM Studio measurement unless marked ✓ Verified.
A second reply while offline confirms that the model is running on this Mac.
This report names an exact Hugging Face repository and GGUF quant. LM Studio lets you search that exact source, choose the matching quant, download it, and chat without using Terminal.
An open-source GGUF alternative with friendly hardware-fit hints.
Its MLX engine is experimental, and support for new model architectures can lag.A trusted Ollama catalog model, or later use with coding tools and a local API.
An Ollama package may use different weights or a different quant from this report.One interface for GGUF, MLX, Ollama, documents, and knowledge workflows.
It exposes more choices than the first-chat path and its free license is for personal use.- Model not listed: paste the exact repository ibm-granite/granite-4.2-30b-GGUF, not only the model nickname.
- Download stalls: confirm there is enough free storage, reconnect to Wi-Fi, and restart the download inside the app.
- Load fails or the app closes: quit memory-heavy apps. In LM Studio, confirm Q2_K is the model currently loaded. Otherwise use a smaller model from this Mac's results.
- No reply while offline: make sure the downloaded local model—not a remote or cloud model—is selected in the chat.
Your anonymous feedback helps us prioritize which Mac and model paths to retest.
Other models on this Mac
Granite 4.2 30B on other MacBook Pro M3 Pro configurations
FAQ
Can the MacBook Pro M3 Pro · 18GB run Granite 4.2 30B?
Yes at Q2_K. We estimate about 14.3GB of working memory and 6.9–9.6 tokens/s at 4K context.
Which Granite 4.2 30B quant should I use on this Mac?
Q2_K. It is a 10.9GB download and leaves about 0.7GB inside our conservative working budget.
Which app should I use for Granite 4.2 30B on this Mac?
Start with LM Studio. This page gives the complete point-and-click walkthrough.
Are these speeds measured on a MacBook Pro M3 Pro?
No. The range is a formula estimate based on memory bandwidth, model size, active parameters, cooling, and a 4K context. The app, backend, thermals, and prompt can change real performance.