Mini
Apple Mac mini (M4 Pro, 48GB)
macOS
M4 Pro with 48GB unified memory (representative high-memory build).
Memory
48 GB
GPUs
1×
RAM
48 GB
Models
29
Type
Mini
Inference Memory
48 GB
Accelerator
48 GB
System RAM
48 GB
OS
macOS
What it can run
29 models| Arcee Trinity Mini 26B | Q8_0 | 14 tok/s | Acceptable |
| Arcee Trinity Nano 6B | Q8_0 | 59 tok/s | Excellent |
| DeepSeek R1 Distill Qwen 7B | Q8_0 | 38 tok/s | Good |
| DeepSeek V3 | Q2_K | – | Not viable |
| Gemma 3 27B | Q5_K_M | 8 tok/s | Acceptable |
| Gemma 4 26B-A4B | Q8_0 | 42 tok/s | Good |
| Gemma 4 31B | Q8_0 | 6 tok/s | Marginal |
| Gemma 4 E2B | Q8_0 | 41 tok/s | Good |
| Gemma 4 E4B | Q8_0 | 25 tok/s | Acceptable |
| GigaChat Lightning 10B | Q8_0 | 61 tok/s | Excellent |
| Llama 3.1 70B Instruct | Q4_K_M | 6 tok/s | Acceptable |
| Llama 3.1 8B Instruct | Q8_0 | 32 tok/s | Good |
| Llama 3.2 11B Vision | Q8_0 | 30 tok/s | Good |
| Llama 3.2 1B Instruct | Q8_0 | 90 tok/s | Excellent |
| Llama 3.2 3B Instruct | Q8_0 | 60 tok/s | Excellent |
| Llama 3.3 70B Instruct | Q4_K_M | 12 tok/s | Acceptable |
| Llama 4 Scout | Q3_K_M | 6 tok/s | Marginal |
| nomic-embed-text v1.5 | FP16 | – | Excellent |
| NVIDIA Nemotron-3-super-120B-A12B | Q2_K | 50 tok/s | Good |
| Phi-4 14B | Q5_K_M | 35 tok/s | Good |
| Phi-4 Mini | Q8_0 | 55 tok/s | Excellent |
| Qwen 2.5 Coder 32B Instruct | Q4_K_M | 10 tok/s | Acceptable |
| Qwen3-14B Instruct | Q8_0 | 25 tok/s | Good |
| Qwen3.5-122B-A10B | Q5_K_M | 36 tok/s | Good |
| Qwen3.5-27B | Q8_0 | 9 tok/s | Acceptable |
| Qwen3.5-397B (MoE) | Q2_K | – | Not viable |
| Qwen3.6-27B | Q8_0 | 9 tok/s | Acceptable |
| Stable Diffusion 3.5 Large | FP16 | – | Acceptable |
| Whisper Large V3 Turbo | FP16 | – | Excellent |
Showing 29 of 29 entries
Best Fit
Who this machine makes sense for
This machine is a buy-it-ready path for users who want predictable local AI performance without building from parts. 48 GB gives it enough headroom to matter for real model selection, not just toy workloads.
Before You Buy
What to verify first
The main check before buying is upgrade path clarity: confirm memory ceiling, storage expandability, and whether the accelerator path still matches the models you expect to run a year from now.