Apple · Compact desktop
Mac Mini M4 (24GB)
Office sweet spot, silent, MLX 2x boost
- 24 GBunified memory
- 14Bfits in memory (Q4, 8k)
- 14Bpractical (estimate)
- 30 Wmax draw
- ~€920indicative price
What can it run?
Pick a job or a model size. The bar compares what it needs with this machine's usable memory.
- Model weights
- Context cache
- Runtime + extras (Whisper, embeddings)
How we calculate this
Weights = parameters × bits per weight / 8 (Q4_K_M ≈ 4.85; Q8_0 ≈ 8.5). Cache = context tokens × the reference model's per-token size (layers × KV heads × head size × 2 × 2 bytes). Plus 1.5 GB of runtime. Usable memory = total minus what the system keeps (3–6 GB on shared memory, 0.5 GB on a GPU). Comfortable = fits in 85%. It is a ±20% estimate: measure it on your machine before you decide. How to pick the GGUF file
When does it beat the cloud?
Set your usage. We compare the purchase plus electricity with what you would pay a cloud API.
| Month | Own hardware | Cloud |
|---|
- Own hardware (purchase + electricity)
- Cloud API
Assumptions: €0.25/kWh (Spain average, editable), USD 1 = €0.92, 3 input tokens per output token, and the machine at maximum draw for every hour it is on (worst case). API prices verified 2026-09-09. Your time and maintenance are not included. Note: the cloud side is a frontier model and here you would run a smaller open one; this compares cost, not quality.
Learn with this machine
- Edge AI Hardware Guide 2026: Jetson vs Mac Mini vs NUCJetson Orin Nano Super, Mac mini M4 and a Core Ultra mini PC compared on vendor specs: memory, TOPS, power and which local models each one can hold.
- Cloud vs Local AI: Real Cost Analysis for Spanish SMEs in 2026Compare the expenses of using cloud APIs like OpenAI against running local hardware on a Mac Mini to determine the best AI strategy for your Spanish SME.
- Google Gemma 3: Open, Multimodal, and It Fits a Mac MiniLearn how to run Google Gemma 3 locally on a Mac Mini to process text and images with privacy and a large context window.
- GGUF Quantization: Pick the Right File for Your MachineHow to read a GGUF file name, choose between Q4_K_M, Q5 and Q8 for the memory you have, and measure speed, memory and quality yourself with three commands.
Skip it if…
- a cloud API already covers you and your volume is low: check the break-even maths.
Specs and where the numbers come from
| CPU | Apple M4 (10-core) |
|---|---|
| GPU | 10-core GPU |
| NPU | 16-core Neural Engine |
| Memory | 24 GB (unified memory); usable by the model ≈ 20 GB |
| Speed | 20 tok/s with 14B vendor or community estimate, not measured by us |
| Price | ~€920 indicative, checked 2026-09-19; check the live price in the shop |
We only call something "measured" when it ran on our machines. Editorial policy