Macs are among the easiest and most cost-effective ways to run large AI models locally, because Apple Silicon’s unified memory lets the GPU use most of the system RAM. A 64GB or 128GB Mac can hold models that would need several expensive GPUs on a PC. In August 2026, Apple refreshed its desktop line with a Mac mini (M6 and M5 Pro) and a Mac Studio (M5 Max and M5 Ultra), both shipping from September 22. This guide explains which Mac and which memory size to buy for local LLMs.
Quick Recommendations
- Best value starter: Mac mini M6 with 32GB. Enough for 8–14B models and some 20–30B MoE models.
- Best all-rounder: Mac mini M5 Pro with 48–64GB. Comfortable with 27–35B models, with much more bandwidth than the M6.
- Best for 70B-class and ~120B MoE models: Mac Studio M5 Max with 128GB.
- Frontier-scale models: Mac Studio M5 Ultra with 256–512GB.
The 2026 Mac Desktop Lineup for Local AI
| Mac | Starting price (US) | Memory | Memory bandwidth |
|---|---|---|---|
| Mac mini M6 | $899 (16GB, 256GB SSD) | Up to 32GB | Up to 170GB/s |
| Mac mini M5 Pro | $1,699 (24GB, 512GB SSD) | Up to 64GB | 307GB/s |
| Mac Studio M5 Max | $2,499 (36GB) | Up to 128GB | Up to 614GB/s |
| Mac Studio M5 Ultra | $5,499 | Up to 512GB (512GB ships late October) | Up to 1.2TB/s |
Apple’s 2026 chips also add Neural Accelerators in each GPU core. Apple says these speed up LLM prompt processing substantially compared with the previous generation, which helps most with long prompts and documents.
How Much Memory Should You Buy?
By default, macOS lets the GPU use only part of unified memory, roughly two-thirds to three-quarters depending on total RAM. Plan for that when sizing models. Our Mac VRAM Optimizer explains the limit and how it can be raised.
| Memory | What fits comfortably (4-bit) |
|---|---|
| 16GB | 4–8B models (Gemma 4 E4B, Qwen3 8B) |
| 24–32GB | Up to ~14B dense, plus gpt-oss-20b and some ~30B MoE models with short context |
| 48–64GB | 27–35B models (Qwen3.8-27B, Gemma 4 31B, Qwen3.6-35B-A3B) with generous context |
| 128GB | 70B-class dense models and ~120B MoE models such as gpt-oss-120b |
| 256–512GB | Very large MoE models such as DeepSeek V4-Flash at low-bit quantization |
Check any model with the VRAM Calculator. For the general math, see How Much RAM and VRAM Do You Need?
Estimated Generation Speed
Using tokens/sec ≈ bandwidth × 0.6–0.75 ÷ model size in GB:
| Mac | 8B at 4-bit (~5GB) | 27B at 4-bit (~17GB) | 70B at 4-bit (~42GB) |
|---|---|---|---|
| Mac mini M6, 24GB or 32GB (170GB/s) | ~20–25 tok/s | ~6–8 tok/s | Doesn’t fit |
| Mac mini M5 Pro (307GB/s) | ~37–46 tok/s | ~11–14 tok/s | ~4–5 tok/s (64GB, tight) |
| Mac Studio M5 Max (614GB/s) | ~74–92 tok/s | ~22–27 tok/s | ~9–11 tok/s |
| Mac Studio M5 Ultra (1.2TB/s) | ~140–180 tok/s | ~42–53 tok/s | ~17–21 tok/s |
These are estimates from Apple’s published bandwidth, not our own measurements. MoE models such as Qwen3.6-35B-A3B or gpt-oss-120b generate much faster than dense models of the same size, because only a few billion parameters are active per token.
Should You Buy the Previous Generation?
If you find a good deal, older Macs are still capable. The M4 Pro Mac mini has 273GB/s of bandwidth, the M4 Max Mac Studio up to 546GB/s, and the M3 Ultra Mac Studio 819GB/s with up to 512GB. Memory capacity usually matters more than chip generation: a 64GB M4 Pro can run models that a 32GB M6 can’t.
Mac vs PC GPU
NVIDIA GPUs remain faster per dollar for models that fit in their VRAM, and they’re the standard for fine-tuning. But with 2026 GPU prices inflated by the memory shortage, a Mac is often the simplest and most cost-effective way to run large models quietly. Compare options in our budget GPU guide and Strix Halo vs Apple comparison.
FAQ
How big an LLM can a Mac mini run?
It depends on the memory you order, because the GPU uses the same unified memory as the rest of the system. A Mac mini M6 with 32GB handles 8–14B models and some 20–30B MoE models. An M5 Pro with 48–64GB is comfortable with 27–35B models. macOS normally lets the GPU use only part of total RAM. The Mac VRAM optimizer shows how much that is on your configuration, and how to raise it.
Is the base Mac mini good for local AI?
The 16GB base M6 model handles small models, but it also has less memory bandwidth: Apple lists 153GB/s for the 16GB models and 170GB/s for 24GB and 32GB. For a better experience, choose 32GB or step up to the M5 Pro. Our Mac mini M6 guide compares every configuration.
MLX or llama.cpp on a Mac?
Both work well. LM Studio supports both, and MLX builds are often faster on Apple Silicon. Ollama is the simplest command-line option.
Sources
Apple: new Mac mini, Apple: new Mac Studio, Apple: M6 and M5 Ultra, TechCrunch: Mac mini pricing.
Updated 14 October 2026: M6 bandwidth by configuration and M5 Pro figures confirmed from Apple’s spec page. Updated September 11, 2026: rewritten for the August 2026 Mac mini (M6/M5 Pro) and Mac Studio (M5 Max/M5 Ultra), with clearly labelled estimates.
Work out what your hardware can actually run
Free calculators and directories, sized from real model weights — before you download gigabytes or order a card:
