Sunk Cost sunkcost.ai Data checked 2026-09-03

Can a Mac mini M4 Pro, 24GB run local LLMs?

Yes — 16 of the 48 current models on this site fit in its 16 GB of usable memory, and one more if you keep the window shorter than 32k. The strongest it holds, Gemma 4 12B, runs at 26 tok/s with a 32k window, worked out from memory bandwidth. Whether that saves you money is a different question: at its $1,399 launch price and 500k tokens a day, it pays back in 114 years.

Price$1,399 at launch — discontinued
Memory24 GB, about 16 GB of it addressable by the GPU at 273 GB/s
Best model it runsGemma 4 12B — Below every hosted tier, 26 tok/s estimated
Pay-back against the APIPays back in 114 years at 500k tokens a day

Run the numbers on this machine

What the Mac mini M4 Pro, 24GB 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 16 GB after the weights is how far the context goes. On 3 of the 12 below, this machine's memory is what runs out first: Granite 4.2 8B stops soonest, at 32k. The rest reach 256k, where the calculator's list ends, or the longest setting their own context limit allows.

ModelSpeedClassMemoryLongest context
Gemma 4 12BQ4_K_M 26 tok/s estimated Below every hosted tier 8.0 GB 256k
Qwen3.5 9BQ4_K_M 30 tok/s estimated Below every hosted tier 6.8 GB 256k
MiniCPM5 2BQ4_K_M 69 tok/s estimated Below every hosted tier 3.0 GB 128k
Qwen3.5 4BQ4_K_M 54 tok/s estimated Below every hosted tier 3.8 GB 256k
Ling 3.0 tinyQ4_K_M 80 tok/s estimated Below every hosted tier 5.0 GB 128k
Granite 4.2 8BQ4_K_M 19 tok/s estimated Below every hosted tier 11 GB 32kmemory
gpt-oss-20bMXFP4 28 tok/s estimated Below every hosted tier 13 GB 128k
Gemma 4 E4BQAT Q4_0 24 tok/s estimated Below every hosted tier 5.7 GB 128k
LFM2.5 2.6BQ4_K_M 93 tok/s estimated Below every hosted tier 2.2 GB 128k
Ministral 3 14BQ4_K_M 15 tok/s estimated Below every hosted tier 14 GB 32kmemory
Ministral 3 8BQ4_K_M 21 tok/s estimated Below every hosted tier 9.8 GB 64kmemory
LFM3 1.7BQ4_K_M 136 tok/s estimated not yet placed 1.5 GB 256k

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 273 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 24 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. 3 of the 12 above reach it, and the slowest is 15 tok/s.

4 more fit, and the intelligence index has scored none of them, so the table above cannot place them: Ornith 1.5 9B, Spark-X2.5 4B, Spark-X2.6 4B, LFM2.5 24B-A2B. Their pages show what each one needs and what runs it.

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 five of those at 32k, strongest first: Llama 3.1 8B Instruct at Q4_K_M, Llama 3.1 8B Instruct at Q8_0, Qwen3 14B, 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 Pro, 24GB

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 one published speed taken on this machine, on a superseded model the table above leaves out. It is below, as published and again at 32k of context, which is what every other speed on this page is taken at.

ModelAt 32kAs published
Llama 3.1 8B InstructQ4_K_Msuperseded 22 tok/s measured 42 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 figure comes from heyuan110.com.

One more, at a shorter window

The table above counts what fits at 32k, the context the calculator starts on. One more model fits this machine at a shorter one. Same weights, smaller cache.

ModelLongest window it fitsNeeds thereNeeds at 32k
Devstral Small 2 24BQ4_K_M 8k 16 GB 20 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 16 GB this machine's GPU can use.

Other machines to weigh against the Mac mini M4 Pro, 24GB

MachinePriceMemoryModels that fitPay-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, 16GBdiscontinued $599 16 GB 12 Pays back in 50 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, 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 M5 Pro, 24GB. There are 111 machine match-ups on the site.

The specifics

Chip
M4 Pro — 12-core CPU / 16-core GPU
Memory bandwidth
273 GB/s
Usable by the GPU
16 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
140 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