Apple M3 — Local LLM Performance & Compatibility

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

作者： Jakub Rusinowski · 最后更新： 2026年7月12日

Up to 24 GB unified memory at 100 GB/s — same memory ceiling as M2 but on the 3nm process. Fits 7–8B models at Q4 comfortably. Common in the MacBook Air, iMac, and Mac mini.

Technical Specifications

VRAM	24 GB unified memory
Memory Bandwidth	100 GB/s
TDP	22 W
Architecture	ARM, 3nm TSMC
Release Year	2023
MSRP at Launch	$1,099
Inference Speed (Llama 3.1 8B Q4_K_M)	6.4–13 tok/s (estimated)
Inference Speed (Llama 3.3 70B Q4_K_M)	Does not fit — needs ~44 GB of 18 GB usable

Buy This HardwareApple MacBook Air M3 — 24 GB VRAM · 22 W board power Deploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Apple MacBook Air M3

24 GB VRAM · 22 W board power

2026年价格波动较大——请以当前商品页价格为准。

在亚马逊查看价格

LLMs Compatible with 24 GB Unified Memory

All models below run comfortably in 24 GB unified memory with Q4_K_M quantization.

Llama 3.1 Family	Llama 3.1 8B Instruct · 6 GB VRAM · Q4_K_M · `ollama run llama3.1`
Llama 3.2 Family	Llama 3.2 11B Vision Instruct · 7 GB VRAM · Q4_K_M · llama-3-2
Qwen 2.5 Family	Qwen 2.5 Coder 32B · 20 GB VRAM · Q4_K_M · `ollama run qwen2.5-coder:32b`
Gemma 3	Gemma 3 27B Instruct · 17 GB VRAM · Q4_K_M · `ollama run gemma3:27b`
Phi-4 Mini	Phi-4 Mini (3.8B) · 3 GB VRAM · Q4_K_M · `ollama run phi4-mini`
Mistral Family	Mistral Small 3 (24B) · 15 GB VRAM · Q4_K_M · `ollama run mistral-small`
SmolLM2	SmolLM2 1.7B Instruct · 2 GB VRAM · Q4_K_M · `ollama run smollm2:1.7b`
Qwen3.8	Qwen3.8 27B · 18 GB VRAM · Q4_K_M · `ollama run qwen3.8:27b`

Best Use Cases

8B models (Q4)
MacBook Air
iMac
entry-level

Quick Start with Ollama

Install Ollama then run the recommended model for this GPU:

ollama run llama3.2:3b

FAQ

Can the Apple M3 run local LLMs?

Yes — the Apple M3 has 24 GB unified memory and runs Up to 24 GB unified memory at 100 GB/s — same memory ceiling as M2 but on the 3nm process. Fits 7–8B models at Q4 comfor

How fast is the Apple M3 for AI inference?

The Apple M3 is estimated to run Llama 3.1 8B at 6.4–13 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 18 GB usable. These are modelled estimates, not measurements — see /en/methodology.

What LLMs can I run on 24 GB VRAM?

With 24 GB you can run: Llama 3.1 Family, Llama 3.2 Family, Qwen 2.5 Family, Gemma 3, Phi-4 Mini. Use Ollama for the easiest setup: ollama run llama3.2:3b.

Can I Run It? — Apple M3

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VRAM Tier

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Buying Guide

Best GPU Buyer Guide 2026

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