Apple's most powerful Mac Mini for local AI. Up to 64GB unified memory, 16-core GPU, and whisper-quiet operation. Run Llama 3.1 70B quantized locally.
Price
From $1,399
CPU
Apple M4 Pro (10-core CPU)
GPU
Apple M4 Pro (16-core GPU)
Neural Engine
16-core Neural Engine
Unified Memory
16GB / 32GB / 64GB
Storage
512GB / 1TB / 2TB / 4TB SSD
TDP
~50W (very efficient)
Noise Level
Silent (fanless design)
Token generation speed (tok/s) at batch size 1. Lower quantization = faster but less accurate. Results may vary based on model version and system conditions.
| System | Llama 3.1 70B | Llama 3.1 8B | Mistral 7B | Codestral 22B |
|---|---|---|---|---|
| Mac Mini M4 Pro (64GB) | ~8 tok/s | ~120 tok/s | ~150 tok/s | ~25 tok/s |
| RTX 4070 Super (12GB) | ~12 tok/s | ~180 tok/s | ~220 tok/s | ~35 tok/s |
| RTX 4070 Ti (16GB) | ~18 tok/s | ~250 tok/s | ~300 tok/s | ~50 tok/s |
| Mac Mini M4 (24GB) | Not supported | ~60 tok/s | ~80 tok/s | Not supported |
Note: 70B models require 48GB+ unified memory for Q4 quantization. 16-32GB systems should use 7B-13B models for optimal performance.
| Model | Recommended Quantization | Memory Required | Status |
|---|---|---|---|
| Llama 3.1 70B | Q4_0, Q5_1 | 48GB+ recommended | Works great |
| Llama 3.1 8B | Q4_0 - Q8_0 | 16GB minimum | Excellent |
| Llama 3.2 1B/3B | Q4_0 | 16GB minimum | Excellent |
| Mistral 7B | Q4_0, Q5_1 | 16GB minimum | Excellent |
| Mixtral 8x7B | Q4_0, Q5_1 | 32GB+ recommended | Works well |
| Codestral 22B | Q4_0, Q5_1 | 48GB+ recommended | Works well |
| Gemma 2 27B | Q4_0 | 48GB+ recommended | Works well |
| Qwen 2.5 72B | Q4_0 | 64GB recommended | Needs 64GB |
| Category | Mac Mini M4 Pro | NVIDIA RTX 4070 | Winner |
|---|---|---|---|
| Price (complete system) | $1,399+ (all-in-one) | $1,500-2,000 (GPU + PC build) | Mac Mini |
| VRAM | Unified (16-64GB) | 12-24GB discrete | Depends on config |
| Noise | Silent (passive cooling) | 30-45dB (fans) | Mac Mini |
| 70B model support | With 48-64GB RAM | Requires 24GB VRAM cards | RTX 4090 |
| Power consumption | ~50W max | 300-450W | Mac Mini |
| Portability | Compact desktop | Full tower/SFF build | Mac Mini |
Choose Mac Mini M4 Pro if: You want a silent, compact, all-in-one system for 7B-34B models. Perfect for developers and productivity-focused AI use.
Choose RTX 4070/4090 if: You need to run 70B+ models at full precision or want maximum throughput. Better for dedicated AI workstations.
Setup time: ~5 minutes
Learn MoreSetup time: ~5 minutes
Learn MoreSetup time: ~15 minutes
Learn MoreSetup time: ~10 minutes
Learn MoreYes for most 7B-34B models, and for 70B quantized models when configured with higher unified memory tiers.
Pick M4 Pro for silence and efficiency; pick discrete NVIDIA builds for maximum throughput and broader CUDA-native tooling.
Validate your target models on requirements and compatibility pages, then follow setup guides to deploy your stack.
The Mac Mini M4 Pro (24GB) is our recommended starting point for most users. It handles 7B-13B models excellently and can run 34B models with quantization.