Can I Run Gemma 3n on Mac Studio (M4 Max, 64 GB)?
Written by Jakub Rusinowski · Last updated April 1, 2025
Yes — comfortably
Yes, comfortably — Gemma 3n E4B at Q8_0 needs about 10.3 GB of the 48 GB usable on Mac Studio (M4 Max, 64 GB), leaving ~37.7 GB spare and running at ~53.5 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~53.5 tok/s
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Mac Studio (M4 Max, 64 GB) — what it gives a model
| Usable memory for models | 48 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Desktop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Gemma 3n on Mac Studio (M4 Max, 64 GB): memory by quantization
| Quant | Memory needed | Fits 48 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 17.6 GB | ✓ Yes | 32K | ~32.4 tok/s | 15.7 GB |
| Q8_0 | 10.3 GB | ✓ Yes | 32K | ~53.5 tok/s | 8.3 GB |
| Q6_K | 8.4 GB | ✓ Yes | 32K | ~64.4 tok/s | 6.4 GB |
| Q5_K_M | 7.5 GB | ✓ Yes | 32K | ~70.9 tok/s | 5.6 GB |
| Q4_K_M | 6.7 GB | ✓ Yes | 32K | ~78.5 tok/s | 4.7 GB |
| Q3_K_M | 5.3 GB | ✓ Yes | 32K | ~95.9 tok/s | 3.3 GB |
| Q2_K | 4.5 GB | ✓ Yes | 32K | ~109.1 tok/s | 2.6 GB |
Which Gemma 3n sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Gemma 3n E4B | 6.7 GB | ✓ Fits | ~78.5 tok/s |
| Gemma 3n E2B | 5.1 GB | ✓ Fits | ~117.2 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.
Mac Studio M4 Max 64 GB limitations
- Memory is soldered; the configuration chosen at purchase is permanent.
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 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 Gemma 3n on Mac Studio (M4 Max, 64 GB)?
Yes, comfortably — Gemma 3n E4B at Q8_0 needs about 10.3 GB of the 48 GB usable on Mac Studio (M4 Max, 64 GB), leaving ~37.7 GB spare and running at ~53.5 tok/s (estimated), with room for about 32,768 tokens of context.
Which quantization of Gemma 3n should I use on Mac Studio (M4 Max, 64 GB)?
Q8_0 — it needs about 10.3 GB of the 48 GB available, downloads as roughly 8.3 GB, and runs at an estimated 53.5 tokens/sec with up to 32K of context.
What limits Gemma 3n on Mac Studio (M4 Max, 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 Computers
Other Models on Mac Studio (M4 Max, 64 GB)
- Gemma 4 on Mac Studio (M4 Max, 64 GB)
- GLM-4.7 / GLM-Z1 on Mac Studio (M4 Max, 64 GB)
- GLM-5 / GLM-5.1 on Mac Studio (M4 Max, 64 GB)
- GLM-6 on Mac Studio (M4 Max, 64 GB)
- GPT-OSS on Mac Studio (M4 Max, 64 GB)
Gemma 3n on GPUs
- Gemma 3n on NVIDIA GeForce RTX 5060 Ti 8GB
- Gemma 3n on NVIDIA GeForce RTX 5060
- Gemma 3n on NVIDIA GeForce RTX 4060
- Gemma 3n on NVIDIA GeForce RTX 3080 (10GB)