Versus Engine
Mac Mini M4 Pro (64GB) vs Nvidia GeForce RTX 5090 (32GB)
Specs, price and the one trade-off that actually decides it — Mac Mini M4 Pro (64GB) against Nvidia GeForce RTX 5090 (32GB), side by side.
Cheaper to start
Tie
Both start at a similar price.
Rated higher
Nvidia GeForce RTX 5090 (32GB)
9.7 vs 9.5 on our design scale.
Standout
Mac Mini M4 Pro (64GB)
64GB unified memory accessible by GPU
Mac Mini M4 Pro (64GB)
Compact unified-memory system built on the Apple M4 Pro with 64 GB shared between CPU and GPU. Runs Gemma 3 27B and Qwen3 30B-A3B at roughly 35-50 tokens/s while operating near-silently — the mid tier of this index for local AI work.
Where it wins, where it doesn't
Pros
- 64GB unified memory accessible by GPU
- Near-silent operation at 100% load
- Class-leading performance-per-watt
Cons
- Zero post-purchase upgradeability
- Lacks native CUDA ecosystem support
Specifications
- chipApple M4 Pro
- tiermid
- example_modelsGemma 3 27B, Qwen3 30B-A3B
- tokens_per_second35-50
- unified_memory_gb64
- memory—
- cuda_cores—
- memory_bus—
- architecture—
- recommended_psu—
- memory_bandwidth—
- total_graphics_power—
Nvidia GeForce RTX 5090 (32GB)
The fastest consumer card available, with 32GB of GDDR7 — and the power bill to match.
Where it wins, where it doesn't
Pros
- 32GB GDDR7 — runs 70B-class models quantised on a single card
- Fastest consumer silicon available
- Avoids the complexity of a multi-GPU build
Cons
- Roughly double the 5080's price for far less than double the performance
- 600W-class power delivery dictates case and PSU choices
- Poor value for anything that is not memory-bound
Specifications
- chip—
- tier—
- example_models—
- tokens_per_second—
- unified_memory_gb—
- memory32GB GDDR7
- cuda_cores21760
- memory_bus512-bit
- architectureBlackwell
- recommended_psu1000W
- memory_bandwidth1792 GB/s
- total_graphics_power575W