2026 Mac mini: Price, M6 vs. M5 Pro & How It Runs AI Agents

Apple announced the 2026 Mac mini on 25 August, with two chips and a striking split in what it chose to measure. The M6 gets the headline: first-ever dual Neural Engine, up to 4.8× the M4. The M5 Pro, an older-generation Pro part, quietly keeps twice the memory bandwidth.

If you are buying this to run AI agents, that second fact is the one that decides your purchase, and it is not the one on the poster.

How much does the 2026 Mac mini cost?

From $899 for the M6 and $1,699 for the M5 Pro, with orders open now and shipping on 22 September. Those are the entry prices; what you will actually spend depends almost entirely on memory.

Apple charges a flat $25 a gigabyte on both chips — $200 for 8GB, $600 for 24GB, $1,000 for 40GB. The memory itself is priced consistently. What is not consistent is where it stops.

The M6 tops out at 32GB. Go to 48GB and Apple changes the chip on you, which is why the step from 32GB to 48GB costs $1,000 rather than the $400 the per-gigabyte rate implies. Storage follows its own ladder: on the M6, 512GB is +$200, 1TB +$500, 2TB +$1,000. Ten-gigabit Ethernet is +$100 on either.

M6 vs M5 Pro: what actually differs?

Cores and clocks on one side, memory and bandwidth on the other. The M6 is the newer design; the M5 Pro is the bigger one.

The dual Neural Engine is genuinely new — Apple calls it a first — and the M6 also brings super cores in the CPU and Neural Accelerators in each GPU core. On Apple’s own numbers it is up to 4.8× an M4, against 4× for the M5 Pro over an M4 Pro.

But look at the bottom row. The M5 Pro moves data between memory and the chip at roughly twice the rate, and that is the number that decides how a local model behaves once it starts writing.

How well does it run AI agents?

Well — and Apple has published half the evidence. Every AI benchmark on Apple’s Mac mini page measures the same thing: time to first token.

Running a model is two jobs. Reading your prompt — prefill, which ends at the first token — is compute-heavy, and that is where the new Neural Engine and GPU accelerators earn their keep. Writing the answer — generation — reads the entire model out of memory for every single token produced, which makes it a bandwidth problem rather than a compute one.

Apple published numbers for the first job and prose for the second. Its M5 Pro section says more unified memory means “faster AI token generation” and attaches no figure. Its M6 section, describing the same class of work, points at “creating AI agents that automate daily tasks” without a generation number either.

You can see why. On Apple’s own specs the M5 Pro has 1.8× the bandwidth of a memory-upgraded M6 and 2.0× that of the base machine — and since generation speed scales with bandwidth, that ratio is roughly the ceiling on how much faster it will write. That is arithmetic from published specs, not a benchmark; nobody has run one, because these ship on 22 September.

For agents specifically, the shape of the work makes both halves matter. An agent loop reads a long context on every step, which is prefill, and then writes tool calls and reasoning, which is generation. The M6 is better at the first. The M5 Pro is better at the second, and has room for models the M6 cannot load at all.

That last constraint is the hard one. Memory decides what you can run; everything else decides how pleasant it is. Apple’s own configurator makes the point for us — the description attached to the M5 Pro’s CPU upgrade names “running large language models” as a reason to pay for it.

Worth knowing if you were considering two boxes instead of one: Apple explicitly describes clustering Mac minis over Thunderbolt 5 at 120Gb/s “to run larger local AI models”, and names exo and LM Studio Bionic as the software for it.

Which one should you buy?

The $1,299 M6 with 32GB, unless you already know you need a bigger model. That is the configuration where the M6’s price advantage and its memory ceiling meet.

• $899, M6, 16GB — fine for agents driving cloud models, and for small local ones. Tight for anything past about 14 billion parameters once you allow for a long context.
• $1,299, M6, 32GB — the value pick. Comfortable for models in the 30B class, and it costs $1,000 less than the cheapest 48GB machine.
• $2,299–$2,699, M5 Pro, 48–64GB — the only way to run 70B-class models locally, and the only way to get 307GB/s. Buy it for the memory, and treat the bandwidth as the bonus that makes it feel quick.

One thing not to buy it for: the Neural Engine headline. The dual 16-core engine is real and the prefill numbers are genuinely large, but if your agent spends its time writing rather than reading, the part of the machine you will feel is the memory bus — and on that measure the cheaper-looking upgrade path is the one that stops at 32GB.

Everything here comes from Apple’s own store and specifications, read on 26 August 2026. The independent benchmarks that would settle the generation question do not exist yet, and will not until these ship on 22 September.