GPUFits
GPUs / Mac mini M4 Pro (48GB)
Mac mini M4 Pro (48GB) for Local LLMs: What It Runs and How Fast
The Mac mini M4 Pro 48GB is the cheapest ticket to “quietly running the 30B tier”: 48GB unified memory (75% ≈ 36GB usable for models), 273 GB/s bandwidth, ~50W whole-system draw, near-silent, at roughly $1,799 (M4 Pro $1,399 + $400 for the 24→48GB upgrade, est.). It runs Qwen3 30B-A3B Q4 comfortably (~21GB, theoretical ~100 tok/s — MoE is the Mac's perfect match), and dense 32B Q4 (~23.7GB) is also in the comfort zone; 70B (~47.4GB) exceeds capacity.
The limitation is bandwidth: 273 GB/s means dense 8B at a theoretical ~42 tok/s — usable but not fast; unified memory can never be upgraded, so commit to the 48GB tier in one step. Profile: desk-space/noise-sensitive users targeting ≤30B who accept the macOS ecosystem (MLX and llama.cpp's Metal backend are both mature). It is very often the machine that pulls people into local LLMs, and regret rates are low.
Specs
| Nominal VRAM | 48 GB |
| Usable VRAM (for models) | 36.0 GB |
| Memory bandwidth | 273 GB/s |
| Type | Unified memory |
| Release year | 2024 |
| MSRP | $1,799 |
| TDP | 50 W |
Apple unified memory is counted at 75% usable for models (the rest serves the system/display).
Value Metrics
Based on MSRP (no used price yet); used prices are market estimates, see commentary for volatility.
Model Verdict Matrix (Q4_K_M @8K)
| Model | VRAM needed | Verdict | Recommended quant | Theoretical speed | |
|---|---|---|---|---|---|
| Llama 3.2 3B | 4.4 GB | Comfortable | FP16 | ≈32 tok/s | Try it → |
| Llama 3.1 8B | 7.5 GB | Comfortable | FP16 | ≈13 tok/s | Try it → |
| Qwen3 8B | 7.7 GB | Comfortable | FP16 | ≈12 tok/s | Try it → |
| Phi-4 14B | 12.2 GB | Comfortable | FP16 | ≈7 tok/s | Try it → |
| Mistral Small 3.2 24B | 17.5 GB | Comfortable | Q8_0 | ≈8 tok/s | Try it → |
| Gemma 3 27B | 22.4 GB | Comfortable | Q8_0 | ≈7 tok/s | Try it → |
| Qwen3.8 27B | 20.7 GB | Comfortable | Q8_0 | ≈7 tok/s | Try it → |
| Muse Glimmer 30B | 20.1 GB | Comfortable | Q8_0 | ≈7 tok/s | Try it → |
| Qwen3 30B-A3B | 21.0 GB | Comfortable | Q8_0 | ≈58 tok/s | Try it → |
| Qwen3 32B | 23.7 GB | Comfortable | Q6_K | ≈8 tok/s | Try it → |
| gpt-oss-20b | 14.7 GB | Comfortable | Q8_0 | ≈53 tok/s | Try it → |
| Llama 3.3 70B | 47.4 GB | Not feasible | Q2_K | ≈7 tok/s | Try it → |
| gpt-oss-120b | 73.6 GB | Not feasible | needs 3 cards | — | Try it → |
| DeepSeek-R1 671B | 413.1 GB | Not feasible | — | — | Try it → |
Theoretical speed = bandwidth × 0.75 ÷ per-token weight bytes (active params for MoE); real-world results vary with framework/driver/CPU, ±30%.
FAQ
- What can the Mac mini M4 Pro 48GB run?
- Usable VRAM is ~36GB at the 75% rule: at Q4 the 32B tier (Qwen3 32B ~23.7GB) is comfortable, and Qwen3 30B-A3B at a theoretical ~100 tok/s is an excellent experience; 70B exceeds capacity.
- Is the M4 Pro fast for LLMs?
- Depends on model type: MoE (3-5B active) theoretically 60-100 tok/s — fluid; dense 8B ~42 tok/s — usable; dense 32B ~10 tok/s — readable but slow. 273 GB/s is the hard ceiling.
- 48GB or 64GB (M4 Max)?
- For ≤30B targets, the 48GB Mac mini is better value; to touch 70B Q4 (~47.4GB) you need a 64GB+ Mac Studio — 48GB yields only ~36GB usable, a full tier short.
Related guides
- Mac vs GPU for LLM Inference: Unified Memory Explained
- MoE Model Hardware Requirements: Total vs Active Parameters
- Run GGUF Models Locally: llama.cpp and Ollama Walkthrough
Try Mac mini M4 Pro (48GB) in the GPU compatibility checker →
Data verified 2026-09-01