Can I Run Nemotron Cascade 2 on Mac mini (M4 Pro, 64 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 11 września 2026
Yes
Yes — Nemotron-Cascade 2 30B-A3B at Q8_0 needs about 36.2 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB) (~11.8 GB spare), at ~29.5 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~29.5 tok/s
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Mac mini (M4 Pro, 64 GB) — what it gives a model
| Usable memory for models | 48 GB |
| Memory bandwidth | 273 GB/s |
| Form factor | Mini PC |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Nemotron Cascade 2 on Mac mini (M4 Pro, 64 GB): memory by quantization
| Quant | Memory needed | Fits 48 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 65.8 GB | ✗ No | — | — | 63.2 GB |
| Q8_0 | 36.2 GB | ✓ Yes | 32K | ~29.5 tok/s | 33.6 GB |
| Q6_K | 28.5 GB | ✓ Yes | 64K | ~35.4 tok/s | 25.9 GB |
| Q5_K_M | 25 GB | ✓ Yes | 64K | ~39 tok/s | 22.4 GB |
| Q4_K_M | 21.7 GB | ✓ Yes | 64K | ~43.1 tok/s | 19.1 GB |
| Q3_K_M | 16.1 GB | ✓ Yes | 128K | ~52.6 tok/s | 13.5 GB |
| Q2_K | 13 GB | ✓ Yes | 128K | ~59.7 tok/s | 10.4 GB |
What to watch out for
- This model does not publish its full attention configuration, so the KV-cache share of these figures is inferred from its parameter count rather than computed exactly.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
Mac mini M4 Pro 64 GB limitations
- M4 Pro memory bandwidth is half the M4 Max's, so large models that fit will still generate roughly half as fast.
Recommended setup
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 64 GB unified memory at 273 GB/s, shared between CPU and GPU.
- macOS reserves a share of unified memory for the system, so not all of it is available to a model.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is inferred from the parameter count because this model does not publish its full attention configuration.
FAQ
Can I run Nemotron Cascade 2 on Mac mini (M4 Pro, 64 GB)?
Yes — Nemotron-Cascade 2 30B-A3B at Q8_0 needs about 36.2 GB of the 48 GB usable on Mac mini (M4 Pro, 64 GB) (~11.8 GB spare), at ~29.5 tok/s (estimated), with room for about 32,768 tokens of context.
Which quantization of Nemotron Cascade 2 should I use on Mac mini (M4 Pro, 64 GB)?
Q8_0 — it needs about 36.2 GB of the 48 GB available, downloads as roughly 33.6 GB, and runs at an estimated 29.5 tokens/sec with up to 32K of context.
What limits Nemotron Cascade 2 on Mac mini (M4 Pro, 64 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Models on Mac mini (M4 Pro, 64 GB)
- Nex-N2 on Mac mini (M4 Pro, 64 GB)
- Nex-N2.5 on Mac mini (M4 Pro, 64 GB)
- North Mini Code on Mac mini (M4 Pro, 64 GB)
- OLMo 2 on Mac mini (M4 Pro, 64 GB)
- Phi 3.5 Family on Mac mini (M4 Pro, 64 GB)
Nemotron Cascade 2 on GPUs
- Nemotron Cascade 2 on NVIDIA GeForce RTX 5090
- Nemotron Cascade 2 on NVIDIA GeForce RTX 5080
- Nemotron Cascade 2 on NVIDIA GeForce RTX 5070 Ti
- Nemotron Cascade 2 on NVIDIA GeForce RTX 5070
What This Model Is Good At
Model & Tools
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