Can I Run Llama 3.2 Family on MacBook Pro 14" (M4 Pro, 24 GB)?

Written by Jakub Rusinowski · Last updated August 15, 2026

MacBook Pro 14" (M4 Pro, 24 GB) — what it gives a model

Usable memory for models	18 GB
Memory bandwidth	273 GB/s
Form factor	Laptop
Operating system	macOS
Memory upgradeable	No — soldered
Price	$1,999 (lib/data/laptops.ts (street price), checked 2026-07-06)

Llama 3.2 Family on MacBook Pro 14" (M4 Pro, 24 GB): memory by quantization

Quant	Memory needed	Fits 18 GB?	Max context	Est. speed	Download
F16	23.3 GB	✗ No	—	—	21.2 GB
Q8_0	13.4 GB	✓ Yes	32K	~12.1 tok/s	11.3 GB
Q6_K	10.8 GB	✓ Yes	32K	~15.2 tok/s	8.7 GB
Q5_K_M	9.7 GB	✓ Yes	32K	~17.3 tok/s	7.5 GB
Q4_K_M	8.5 GB	✓ Yes	64K	~19.9 tok/s	6.4 GB
Q3_K_M	6.7 GB	✓ Yes	64K	~26.5 tok/s	4.5 GB
Q2_K	5.6 GB	✓ Yes	64K	~32.5 tok/s	3.5 GB

Which Llama 3.2 Family sizes fit

Variant	Needs at Q4_K_M	Fits?	Est. speed
Llama 3.2 90B Vision Instruct	57.8 GB	✗ Too large	—
Llama 3.2 11B Vision Instruct	8.5 GB	✓ Fits	~19.9 tok/s
Llama 3.2 3B Instruct	3.7 GB	✓ Fits	~52.4 tok/s
Llama 3.2 1B Instruct	1.8 GB	✓ Fits	~112.4 tok/s

What to watch out for

• 1 larger variant of Llama 3.2 Family does not fit and would need CPU offload or different hardware.
• Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.

MacBook Pro M4 Pro 24 GB limitations

• Unified memory is soldered and cannot be upgraded after purchase.
• 24 GB is the practical ceiling for a single mid-size model plus a long context.

Recommended setup

Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput

How these numbers are calculated

• Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
• 24 GB unified memory at 273 GB/s, shared between CPU and GPU.
• macOS reserves a share of unified memory for the system, so not all of it is available to a model.
• Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
• KV cache is computed from this model's published attention configuration.

FAQ

Can I run Llama 3.2 Family on MacBook Pro 14" (M4 Pro, 24 GB)?

Yes, comfortably — Llama 3.2 11B Vision Instruct at Q8_0 needs about 13.4 GB of the 18 GB usable on MacBook Pro 14" (M4 Pro, 24 GB), leaving ~4.6 GB spare and running at ~12.1 tok/s (estimated), with room for about 32,768 tokens of context.

Which quantization of Llama 3.2 Family should I use on MacBook Pro 14" (M4 Pro, 24 GB)?

Q8_0 — it needs about 13.4 GB of the 18 GB available, downloads as roughly 11.3 GB, and runs at an estimated 12.1 tokens/sec with up to 32K of context.

What limits Llama 3.2 Family on MacBook Pro 14" (M4 Pro, 24 GB)?

Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.

Which runtime should I use?

Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput

Other Computers

• Llama 3.2 Family on MacBook Pro M4 Max 128 GB
• Llama 3.2 Family on MacBook Pro M4 Max 48 GB
• Llama 3.2 Family on MacBook Air M4 16 GB
• Llama 3.2 Family on MacBook Pro M5 Max 128 GB

Other Models on MacBook Pro 14" (M4 Pro, 24 GB)

• Llama 3.2 Vision on MacBook Pro 14" (M4 Pro, 24 GB)
• Ministral on MacBook Pro 14" (M4 Pro, 24 GB)
• Mistral Family on MacBook Pro 14" (M4 Pro, 24 GB)
• Mistral Small 3.1 on MacBook Pro 14" (M4 Pro, 24 GB)
• Nemotron Cascade 2 on MacBook Pro 14" (M4 Pro, 24 GB)

Llama 3.2 Family on GPUs

• Llama 3.2 Family on NVIDIA GeForce RTX 5070
• Llama 3.2 Family on NVIDIA GeForce RTX 5060 Ti 8GB
• Llama 3.2 Family on NVIDIA GeForce RTX 5060
• Llama 3.2 Family on NVIDIA GeForce RTX 4070 Ti

What This Model Is Good At

• Best local LLMs for general assistant
• Best local LLMs for rag
• Best local LLMs for writing

Model & Tools

• Llama 3.2 Family model page
• VRAM calculator
• Check your own hardware

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