Mac mini, Mac Studio or NVIDIA AI workstation: which one for local AI in 2026?

Apple released the new Mac mini M6 and M5 Pro in late September, and our customers all ask us the same question: is a Mac mini enough to run AI locally, or do you need a workstation with an NVIDIA graphics card? The answer comes down to two numbers: how much memory is available for the model, and how fast that memory is. Here is our comparison, based on public figures.

For the full overview of machines, see our guide AI PC: which computer for local AI?

The verdict in 30 seconds

• A personal assistant with a 7 to 14 billion parameter model: a 24 GB Mac mini M5 Pro does the job, silently. An RTX 5070 Ti workstation writes about 2.7 times faster and reads documents more than 4 times faster, for about €1,000 more.
• 30 to 70 billion parameter models just for you: the 64 GB Mac mini M5 Pro loads models that no 16 or 32 GB card can hold, but it answers slowly.
• A small team, long documents, image generation: an NVIDIA workstation. It serves several computers on your network and runs every tool built for CUDA (ComfyUI, vLLM, fine-tuning).
• Models larger than 64 GB: Mac Studio M5 Ultra (up to 512 GB), GB10 workstation (128 GB, with CUDA) or Threadripper workstation with RTX PRO 6000 cards (96 to 288 GB).

The machines compared

Prices checked on 26 October 2026 at Apple and major French retailers. On a Mac, unified memory is shared with macOS and your applications: count a few gigabytes less than the total capacity for the model.

What the measurements say

To compare without bias, we use the llama.cpp reference test (llama.cpp is the engine behind Ollama and LM Studio): the same model (Llama 2 7B, compressed to 4 bits) on every machine. Two numbers matter: how fast the model reads the text you give it (your question, your documents) and how fast it writes the answer. A token is roughly a word or part of a word.

Results published by the llama.cpp community (Metal for Apple chips, CUDA for NVIDIA cards). They were measured by different users: they give an order of magnitude, not a lab result.

Two takeaways:

• For writing, an RTX 5070 Ti is about 2.7 times faster than a Mac mini M5 Pro, and an RTX 5060 Ti 1.4 times faster.
• For reading, the gap widens: more than 4 times with the RTX 5070 Ti. As a rough guide, a 20,000-token contract is read in about 3 seconds by the RTX 5070 Ti, versus around twelve seconds by the Mac mini M5 Pro. That is the wait you feel when you ask a question about a long document.

The Mac's advantage lies elsewhere: capacity. A 70 billion parameter model compressed to 4 bits weighs about 40 GB. It fits in a 64 GB Mac mini M5 Pro, but in no consumer graphics card. However, every word written requires reading the whole model from memory again: at 307 GB/s, the theoretical limit is about 7 tokens per second. That is usable for one patient person, not for a team.

Mac mini: strengths and limits

Strengths

• Silent (4 to 5 dBA at idle according to Apple) and frugal: 155 W maximum continuous power
• Up to 64 GB of memory available to the GPU in a 12.7 cm box
• Well supported by Ollama, LM Studio and MLX, Apple's framework
• On the M5 Pro, several Mac minis can be linked over Thunderbolt 5 to run a larger model

Limits

• Memory is chosen at purchase and can never be added: going from 24 to 64 GB almost doubles the price (€1,999 to €3,649, with a better processor and SSD)
• No CUDA: vLLM, most fine-tuning tools and many ComfyUI extensions are built for NVIDIA
• Reading long documents is several times slower
• Not well suited to an assistant shared by several people at the same time

NVIDIA AI workstation: strengths and limits

Strengths

• Faster on models that fit in its video memory: with an RTX 5070 Ti, 2.7 times faster at writing and more than 4 times faster at reading than a Mac mini M5 Pro
• CUDA: every AI tool works, from Ollama to vLLM, ComfyUI, Flux and fine-tuning
• Upgradable: our 16 GB Essential workstation accepts a second RTX 5060 Ti, to move to 32 GB without changing machines
• Delivered ready to use: Linux, NVIDIA drivers and CUDA, Ollama and a chat interface reachable from every computer on your network

Limits

• Bulkier and louder than a Mac mini, with an 850 to 1,200 W power supply depending on the configuration
• 16 or 32 GB of video memory: beyond 30 billion parameters, you need a professional card such as the RTX PRO 6000

What about the Mac Studio?

The Mac Studio M5 Max (from €2,999, up to 128 GB) writes faster than an RTX 5060 Ti in the test above (120 tokens per second versus 91), but slower than an RTX 5070 Ti (177), and reads half as fast as the latter. The M5 Ultra (from €6,599) goes up to 512 GB of unified memory at 1.2 TB/s: it is the reference machine for running very large models on your own, provided you accept the price of the options (going from 96 to 256 GB costs €4,400 more) and the lack of CUDA.

At comparable capacity, the GB10 workstation (128 GB) keeps the NVIDIA ecosystem, and the Threadripper workstation combines large memory and speed for a whole team. We cover the GB10 in detail in our DGX Spark review.

Our advice by use case

Our ready-to-use AI workstations

We assemble, install and test every workstation before shipping, with the models of your choice already downloaded. New product, tested and delivered in 7 days, manufacturer warranty on every component and after-sales service in France. For workstations on quote, you can reserve with a deposit, refunded in full if you decline the quote.

Torn between a Mac and a workstation? Tell us about your use (number of users, types of documents, target model) and we will advise you: contact us or call +33 6 32 49 26 41. The full range is on our GPU & AI page.

Read also

• RTX 5060 Ti 16 GB or RTX 5070 Ti for AI?
• AI graphics cards: 2026 ranking and comparison
• NVIDIA DGX Spark: price, review and alternatives
• To choose the model: our pick of the best local LLM

Frequently asked questions

Which Mac mini should I choose for AI? The M5 Pro: it has twice the bandwidth of the M6 (307 GB/s versus 153 to 170 GB/s). Take 48 or 64 GB if you are aiming for models of 30 billion parameters and more, because memory cannot be added later.

Is the Mac mini M6 enough for local AI? For small models, up to about 8 billion parameters, yes. With 16 to 32 GB shared with the system and modest bandwidth, it remains a secondary machine for AI.

Does Ollama run on a Mac mini? Yes. Ollama and LM Studio use the GPU of Apple chips through Metal, with no special setup.

Mac mini or DGX Spark? The DGX Spark, or our GB10 workstation, offers 128 GB of memory, twice the largest Mac mini, with similar bandwidth (273 GB/s) and the CUDA ecosystem. The Mac mini is cheaper and more versatile as a desktop computer.

Mac mini or RTX workstation for a business? The workstation: it answers faster, serves several computers at the same time and runs the professional tools built for NVIDIA. It can also be hosted with us in France.

Sources

• Apple, Mac mini (M6 or M5 Pro): technical specifications and Mac mini M6 and M5 Pro announcement (25 August 2026)
• MacG, Mac mini M6 and M5 Pro review (5 October 2026)
• Prices checked on 26 October 2026: Mac mini M5 Pro 24 GB (Consomac), M5 Pro 48 GB (Darty, Fnac), M5 Pro 64 GB (LDLC Pro)
• Consomac, Mac Studio M5 Max and M5 Ultra: prices in France and OWC, M5 Max and M5 Ultra specifications
• llama.cpp, performance on Apple chips (discussion #4167) and performance on NVIDIA cards (discussion #15013), accessed 26 October 2026