| Model & Quantization | VRAM Demand | Apple Mac mini M4 Pro | NVIDIA GeForce RTX 5090 |
|---|---|---|---|
| Meta LLaMA 3.3 70B (IQ4_XS, 4k FP8 KV) | 41.9 GB | Fits w/ sysctl (~5.5 tok/s) | Exceeds VRAM (-9.9GB) |
| Alibaba Qwen3-Coder 30B-A3B (Q4_K_M) | 20.7 GB | Runs Comfortably (~85 tok/s MLX) | Runs Comfortably (~155 tok/s) |
| Google Gemma 4 31B (Q4_K_M, 128k FP8 KV) | 30.6 GB | Fits Comfortably (After sysctl) | Tight Fit (+1.4GB, ~68 tok/s) |
| Alibaba Wan 2.1 14B 720p (FP8) | 28.4 GB | Fits RAM (Very Slow MPS Render) | Runs Comfortably (+3.6GB Native FP8) |
| Qwen 2.5 Coder 32B (Q4_K_M, 32k FP8 KV) | 25.6 GB | Runs Comfortably (~11 tok/s) | Runs Comfortably (~68 tok/s) |
Architecturally, these systems target polar-opposite bottlenecks. Apple's M4 Pro fuses 14 CPU cores and 20 GPU cores onto a shared LPDDR5X fabric clocked at 273 GB/s, sipping 5W at idle and ~45W–65W under sustained MLX inference while bypassing PCIe host transfers. Because sparse Mixture-of-Experts coders like `Qwen3-Coder 30B-A3B` only read 3.3B active weights per token, M4 Pro feels shockingly agile—though dense 32B decoding drops to ~11 tok/s and 70B settles around ~5.5 tok/s. NVIDIA's GB202 silicon pairs 21,760 CUDA cores and 680 fifth-generation Tensor Cores with sixteen 32-bit 28 Gbps GDDR7 channels (1,792 GB/s) inside a 575W–600W PCIe 5.0 card. Hardware `NVFP4`/`MXFP4` microscaling and massive raw FLOPS make GB202 6.5x faster on memory reads and over 10x quicker at Wan 2.1 14B FP8 (`28.36 GB`) video generation and 32k prompt ingestion.
On a 48GB Mac mini M4 Pro, Darwin's default 75% wired limit (`36 GB`) rejects 70B checkpoints; run `sudo sysctl iogpu.wired_limit_mb=44032` so 43 GB opens for 70B `IQ4_XS` (`41.91 GB` at 4k FP8 KV). On RTX 5090, pass `--n-cpu-moe` or run Gemma 4 31B at `Q6_K` (`~29.2 GB`).
Matched Upgrade: Unlike the self-contained 45W Mac mini, a bare $2,299 RTX 5090 pulls up to 600W alone; pairing it with a Corsair RM1200x SHIFT ATX 3.1 PSU supplies native 12V-2x6 wiring and clean excursion margin.
1200W ATX 3.1 PSU on Amazon Prime ↗Zero monthly subscriptions, 100% private inference, and unmetered tokens for your homelab or workstation.
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Yes, once you override macOS's default 36GB Metal cap via `sudo sysctl iogpu.wired_limit_mb=44032`. Using MLX 4-bit DWQ or GGUF `IQ4_XS` (`41.91 GB`), 70B checkpoints run locally without SSD swap at roughly 5–6 tok/s while keeping 5GB free for Darwin.
GDDR7 capacity is fixed at 32GB on RTX 5090, leaving dense 70B Q4_K_M (`46.10 GB`) 14.1 GB short. Buyers must budget an extra $900+ for host PC parts too, though cloud rentals easily cover occasional 70B bursts.
Inspect exact KV-cache formulas, test 32k/128k context allocations, or compare cloud rental break-even costs in the interactive matchmaker.
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