Can I Run MiniMax M2.5 on MacBook Pro 16" (M4 Max, 128 GB)?
Written by Jakub Rusinowski · Last updated February 15, 2026
Technically yes, but not recommended
It loads, but it is not worth running — MiniMax M2.5 230B at Q2_K fits in MacBook Pro 16" (M4 Max, 128 GB)'s 96 GB, yet the memory bandwidth limits it to ~3.8 tok/s (estimated), well below usable interactive speed.
Confidence: medium · Recommended quantization: Q2_K · Estimated speed: ~3.8 tok/s
MacBook Pro 16" (M4 Max, 128 GB) — what it gives a model
| Usable memory for models | 96 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
MiniMax M2.5 on MacBook Pro 16" (M4 Max, 128 GB): memory by quantization
| Quant | Memory needed | Fits 96 GB? | Max context | Est. speed | Download |
|---|
| F16 | 464.3 GB | ✗ No | — | — | 460 GB |
| Q8_0 | 248.7 GB | ✗ No | — | — | 244.4 GB |
| Q6_K | 192.9 GB | ✗ No | — | — | 188.6 GB |
| Q5_K_M | 167.3 GB | ✗ No | — | — | 163 GB |
| Q4_K_M | 143.2 GB | ✗ No | — | — | 138.9 GB |
| Q3_K_M | 102.4 GB | ✗ No | — | — | 98 GB |
| Q2_K | 79.9 GB | ✓ Yes | 32K | ~3.8 tok/s | 75.6 GB |
What to watch out for
- At ~3.8 tok/s this loads but is too slow for interactive use — expect roughly 16 seconds per 60 tokens.
- Q2_K is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 1 larger variant of MiniMax M2.5 does not fit and would need CPU offload or different hardware.
- 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.
MacBook Pro M4 Max 128 GB limitations
- Unified memory is soldered — the 128 GB decision is permanent and cannot be upgraded later.
- Sustained decode speed on battery is materially below the plugged-in figures quoted here.
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.
- 128 GB unified memory at 546 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 MiniMax M2.5 on MacBook Pro 16" (M4 Max, 128 GB)?
It loads, but it is not worth running — MiniMax M2.5 230B at Q2_K fits in MacBook Pro 16" (M4 Max, 128 GB)'s 96 GB, yet the memory bandwidth limits it to ~3.8 tok/s (estimated), well below usable interactive speed.
Which quantization of MiniMax M2.5 should I use on MacBook Pro 16" (M4 Max, 128 GB)?
Q2_K — it needs about 79.9 GB of the 96 GB available, downloads as roughly 75.6 GB, and runs at an estimated 3.8 tokens/sec with up to 32K of context.
What limits MiniMax M2.5 on MacBook Pro 16" (M4 Max, 128 GB)?
Memory bandwidth. The model fits, but at 546 GB/s it can only be read fast enough for roughly 3.8 tokens/sec.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Computers
Other Models on MacBook Pro 16" (M4 Max, 128 GB)
MiniMax M2.5 on GPUs
What This Model Is Good At
Model & Tools
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