Can a Mac mini M4, 16GB run local LLMs?
Yes — 12 of the 48 current models on this site fit in its 10.5 GB of usable memory, and two more if you keep the window shorter than 32k. The strongest it holds, Gemma 4 12B, runs at 11 tok/s with a 32k window, worked out from memory bandwidth. Whether that saves you money is a different question: at its $599 launch price and 500k tokens a day, it pays back in 50 years.
Run the numbers on this machine
What the Mac mini M4, 16GB runs
They do not all hold the same window. The weights are a fixed size, but the key-value cache grows with every token you keep, so what is left of 10.5 GB after the weights is how far the context goes. On 7 of the 12 below, this machine's memory is what runs out first: Ministral 3 8B stops soonest, at 32k. The rest reach 256k, where the calculator's list ends, or the longest setting their own context limit allows.
| Model | Speed | Class | Memory | Longest context |
|---|---|---|---|---|
| Gemma 4 12BQ4_K_M | 11 tok/s estimated | Below every hosted tier | 8.0 GB | 128kmemory |
| Qwen3.5 9BQ4_K_M | 13 tok/s estimated | Below every hosted tier | 6.8 GB | 128kmemory |
| MiniCPM5 2BQ4_K_M | 30 tok/s estimated | Below every hosted tier | 3.0 GB | 128k |
| Qwen3.5 4BQ4_K_M | 24 tok/s estimated | Below every hosted tier | 3.8 GB | 128kmemory |
| Ling 3.0 tinyQ4_K_M | 35 tok/s estimated | Below every hosted tier | 5.0 GB | 128k |
| Gemma 4 E4BQAT Q4_0 | 10 tok/s estimated | Below every hosted tier | 5.7 GB | 128k |
| LFM2.5 2.6BQ4_K_M | 41 tok/s estimated | Below every hosted tier | 2.2 GB | 128k |
| Ministral 3 8BQ4_K_M | 9.2 tok/s estimated | Below every hosted tier | 9.8 GB | 32kmemory |
| LFM3 1.7BQ4_K_M | 60 tok/s estimated | not yet placed | 1.5 GB | 256k |
| Ornith 1.5 9BQ4_K_M | 13 tok/s estimated | not yet placed | 6.9 GB | 128kmemory |
| Spark-X2.5 4BQ4_K_M | 23 tok/s estimated | not yet placed | 3.9 GB | 128kmemory |
| Spark-X2.6 4BQ4_K_M | 19 tok/s estimated | not yet placed | 4.8 GB | 128kmemory |
Speed and memory are at 32k context, the setting the calculator starts on; the memory column is the weights plus the cache for that much of it. Each speed says how it was arrived at, and every one here is estimated from this machine's 120 GB/s of memory bandwidth rather than taken from a published benchmark. There is a page on how that sum works, and what each size needs, and one on what 16 GB runs, machine by machine. The longest context is the longest setting the calculator offers that this machine still holds the model at, cache included, and each one opens the calculator on that model at that length. A figure tagged memory is one this machine ran out of room for, and the rest are stopped by the model's own limit or by the end of the list.
For scale, the calculator starts from 80 tok/s for a hosted API and times a local machine against it. Nothing above reaches it, and the quickest is 60 tok/s.
The 48 counted above are the current models. This site prices 16 superseded ones as well, because people still run them, and this machine holds three of those at 32k, strongest first: Llama 3.1 8B Instruct at Q4_K_M, Qwen3 8B, Gemma 3 12B it. Each of those pages asks whether the model is still worth running.
What has been measured on the Mac mini M4, 16GB
Not one of the speeds above was measured on this machine, and that is not because nobody has run a model on one. This site holds two published speeds taken on this machine, both on superseded models the table above leaves out. They are below, as published and again at 32k of context, which is what every other speed on this page is taken at.
| Model | At 32k | As published |
|---|---|---|
| Llama 3.1 8B InstructQ4_K_Msuperseded | 11 tok/s measured | 21 tok/smeasured at an empty window |
| Qwen3 8BQ4_K_Msuperseded | 9.9 tok/s measured | 20 tok/smeasured at an empty window |
A published figure is what its source reports, at the window the model was run at. The 32k figure is that measurement read at 32k of context: every token generated reads the weights and the whole key-value cache, so the longer the window the slower it runs. The figures come from macyou.co, halfpennymac.com.
Two more, at a shorter window
The table above counts what fits at 32k, the context the calculator starts on. Two more models fit this machine at a shorter one. Same weights, smaller cache.
| Model | Longest window it fits | Needs there | Needs at 32k |
|---|---|---|---|
| Granite 4.2 8BQ4_K_M | 16k | 8.0 GB | 11 GB |
| Ministral 3 14BQ4_K_M | 8k | 9.6 GB | 14 GB |
Each window is the longest setting the calculator offers that this machine still holds the model at, and it opens the calculator on that model at that length. The memory figures are the weights plus the key-value cache at that window, against the 10.5 GB this machine's GPU can use.
Other machines to weigh against the Mac mini M4, 16GB
| Machine | Price | Memory | Models that fit | Pay-back |
|---|---|---|---|---|
| The rest of the Mac mini range | ||||
| Mac mini M6, 16GB | $899 | 16 GB | 12 | Pays back in 71 years |
| Mac mini M6, 24GB | $1,099 | 24 GB | 16 | Pays back in 85 years |
| Mac mini M6, 32GB | $1,299 | 32 GB | 22 | Pays back in 82 years |
| Mac mini M5 Pro, 24GB | $1,699 | 24 GB | 16 | Pays back in 135 years |
| Mac mini M5 Pro, 48GB | $2,299 | 48 GB | 32 | Pays back in 155 years |
| Mac mini M5 Pro, 64GB | $2,699 | 64 GB | 32 | Pays back in 182 years |
| Mac mini M4, 24GBdiscontinued | $799 | 24 GB | 16 | Pays back in 66 years |
| Mac mini M4, 32GBdiscontinued | $999 | 32 GB | 22 | Pays back in 73 years |
| Mac mini M4 Pro, 24GBdiscontinued | $1,399 | 24 GB | 16 | Pays back in 114 years |
| Mac mini M4 Pro, 48GBdiscontinued | $1,799 | 48 GB | 32 | Pays back in 128 years |
| Mac mini M4 Pro, 64GBdiscontinued | $1,999 | 64 GB | 32 | Pays back in 142 years |
| Nearest in price elsewhere on the list | ||||
| Strix Halo Framework Desktop, 32GB | $1,269 | 32 GB | 29 | Pays back in 91 years |
| MacBook Air M5 (13-inch), 16GB | $1,299 | 16 GB | 12 | Pays back in 102 years |
| AMD Radeon AI PRO R9700, 32GB | $1,299card only | 32 GB | 32 | Pays back in 84 years |
| MacBook Pro M5 (14-inch), 16GB | $1,999 | 16 GB | 12 | Pays back in 157 years |
| NVIDIA GeForce RTX 5090, 32GB | $1,999card only | 32 GB | 32 | Pays back in 123 years |
Every row uses the same defaults as the figures above: 500k tokens a day at 15:1 input to output, 32k context, and each machine's strongest model that fits, counted against the same 48 current models. Graphics cards are priced as the card alone, so add the PC around one before comparing it with a complete computer. All seven cards here are ranked by what each one holds.
Head to head with the machine that replaced it: Mac mini M6, 16GB. There are 111 machine match-ups on the site.
The specifics
- Chip
- M4 — 10-core CPU / 10-core GPU
- Memory bandwidth
- 120 GB/s
- Usable by the GPU
- 10.5 GB — macOS lets the GPU wire roughly two-thirds of unified memory by default (llama.cpp discussion #2182: 66.7% at 32 GiB or less, 75% above). Raise it with `sudo sysctl iogpu.wired_limit_mb`. Memory is treated as GB throughout, which is slightly conservative.
- Power under load
- 65 W (published) — Apple's published 'max' figure for this chip (support article 103253), a CPU+GPU stress number; inference typically draws less.
- Availability
- Discontinued 2026-08-25. Launch price; Apple no longer sells it new, so treat as a refurbished/used reference.
- Sources
- Apple Support, Apple Support, Low End Mac