Can I Run Gemma 4 on MacBook Pro 16" (M5 Max, 128 GB)?
Written by Jakub Rusinowski · Last updated June 3, 2026
Yes — comfortably
Yes, comfortably — Gemma 4 31B at Q8_0 needs about 35.5 GB of the 96 GB usable on MacBook Pro 16" (M5 Max, 128 GB), leaving ~60.5 GB spare and running at ~9.7 tok/s (estimated), with room for about 131,072 tokens of context.
Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~9.7 tok/s
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MacBook Pro 16" (M5 Max, 128 GB) — what it gives a model
| Usable memory for models | 96 GB |
| Memory bandwidth | 614 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Gemma 4 on MacBook Pro 16" (M5 Max, 128 GB): memory by quantization
| Quant | Memory needed | Fits 96 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 64.6 GB | ✓ Yes | 128K | ~5.3 tok/s | 62 GB |
| Q8_0 | 35.5 GB | ✓ Yes | 128K | ~9.7 tok/s | 32.9 GB |
| Q6_K | 28 GB | ✓ Yes | 128K | ~12.3 tok/s | 25.4 GB |
| Q5_K_M | 24.6 GB | ✓ Yes | 128K | ~14.1 tok/s | 22 GB |
| Q4_K_M | 21.3 GB | ✓ Yes | 128K | ~16.3 tok/s | 18.7 GB |
| Q3_K_M | 15.8 GB | ✓ Yes | 128K | ~22.2 tok/s | 13.2 GB |
| Q2_K | 12.8 GB | ✓ Yes | 128K | ~27.8 tok/s | 10.2 GB |
Which Gemma 4 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Gemma 4 31B | 21.3 GB | ✓ Fits | ~16.3 tok/s |
| Gemma 4 26B-A4B | 18.2 GB | ✓ Fits | ~78.6 tok/s |
| Gemma 4 12B (Unified) | 9.4 GB | ✓ Fits | ~37.8 tok/s |
| Gemma 4 E4B | 6.8 GB | ✓ Fits | ~52.5 tok/s |
| Gemma 4 E2B | 4.9 GB | ✓ Fits | ~73.3 tok/s |
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.
MacBook Pro M5 Max 128 GB limitations
- Unified memory is soldered and cannot be upgraded after purchase.
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 614 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 Gemma 4 on MacBook Pro 16" (M5 Max, 128 GB)?
Yes, comfortably — Gemma 4 31B at Q8_0 needs about 35.5 GB of the 96 GB usable on MacBook Pro 16" (M5 Max, 128 GB), leaving ~60.5 GB spare and running at ~9.7 tok/s (estimated), with room for about 131,072 tokens of context.
Which quantization of Gemma 4 should I use on MacBook Pro 16" (M5 Max, 128 GB)?
Q8_0 — it needs about 35.5 GB of the 96 GB available, downloads as roughly 32.9 GB, and runs at an estimated 9.7 tokens/sec with up to 128K of context.
What limits Gemma 4 on MacBook Pro 16" (M5 Max, 128 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 Computers
- Gemma 4 on MacBook Pro M4 Max 128 GB
- Gemma 4 on MacBook Pro M4 Max 48 GB
- Gemma 4 on MacBook Pro M4 Pro 24 GB
- Gemma 4 on MacBook Air M4 16 GB
Other Models on MacBook Pro 16" (M5 Max, 128 GB)
- GLM-4.7 / GLM-Z1 on MacBook Pro 16" (M5 Max, 128 GB)
- GLM-5 / GLM-5.1 on MacBook Pro 16" (M5 Max, 128 GB)
- GLM-6 on MacBook Pro 16" (M5 Max, 128 GB)
- GPT-OSS on MacBook Pro 16" (M5 Max, 128 GB)
- Granite 3.0 on MacBook Pro 16" (M5 Max, 128 GB)
Gemma 4 on GPUs
- Gemma 4 on NVIDIA GeForce RTX 5090
- Gemma 4 on NVIDIA GeForce RTX 5080
- Gemma 4 on NVIDIA GeForce RTX 5070 Ti
- Gemma 4 on NVIDIA GeForce RTX 5070