Can I Run Gemma 4 on MacBook Air (M4, 16 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 3 czerwca 2026
Yes, but it is tight
Yes, but it is tight — Gemma 4 12B (Unified) at Q6_K needs about 11.3 GB of the 12 GB usable on MacBook Air (M4, 16 GB), leaving only ~0.7 GB before the runtime starts swapping. Expect ~6.2 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: medium · Recommended quantization: Q6_K · Estimated speed: ~6.2 tok/s
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MacBook Air (M4, 16 GB) — what it gives a model
| Usable memory for models | 12 GB |
| Memory bandwidth | 120 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Gemma 4 on MacBook Air (M4, 16 GB): memory by quantization
| Quant | Memory needed | Fits 12 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 25.4 GB | ✗ No | — | — | 24 GB |
| Q8_0 | 14.2 GB | ✗ No | — | — | 12.8 GB |
| Q6_K | 11.3 GB | ✓ Yes | 32K | ~6.2 tok/s | 9.8 GB |
| Q5_K_M | 9.9 GB | ✓ Yes | 64K | ~7.1 tok/s | 8.5 GB |
| Q4_K_M | 8.7 GB | ✓ Yes | 64K | ~8.2 tok/s | 7.2 GB |
| Q3_K_M | 6.6 GB | ✓ Yes | 64K | ~11.2 tok/s | 5.1 GB |
| Q2_K | 5.4 GB | ✓ Yes | 64K | ~14 tok/s | 3.9 GB |
Which Gemma 4 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Gemma 4 31B | 21.4 GB | ✗ Too large | — |
| Gemma 4 26B-A4B | 17 GB | ✗ Too large | — |
| Gemma 4 12B (Unified) | 8.7 GB | ✓ Fits | ~8.2 tok/s |
| Gemma 4 E4B | 6.8 GB | ✓ Fits | ~11.7 tok/s |
| Gemma 4 E2B | 4.9 GB | ✓ Fits | ~17.4 tok/s |
What to watch out for
- Only ~0.7 GB of headroom at Q6_K: a longer context or a second application can push this into swapping.
- 2 larger variants of Gemma 4 do not fit and would need CPU offload or different hardware.
- 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 Air M4 16 GB limitations
- Fanless: sustained generation throttles on long runs in a way the same chip in a MacBook Pro does not.
- 16 GB unified memory is shared with the OS and every open app.
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.
- 16 GB unified memory at 120 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 computed from this model's published attention configuration.
FAQ
Can I run Gemma 4 on MacBook Air (M4, 16 GB)?
Yes, but it is tight — Gemma 4 12B (Unified) at Q6_K needs about 11.3 GB of the 12 GB usable on MacBook Air (M4, 16 GB), leaving only ~0.7 GB before the runtime starts swapping. Expect ~6.2 tok/s (estimated), with room for about 32,768 tokens of context.
Which quantization of Gemma 4 should I use on MacBook Air (M4, 16 GB)?
Q6_K — it needs about 11.3 GB of the 12 GB available, downloads as roughly 9.8 GB, and runs at an estimated 6.2 tokens/sec with up to 32K of context.
What limits Gemma 4 on MacBook Air (M4, 16 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
Other Models on MacBook Air (M4, 16 GB)
- GLM-4.7 / GLM-Z1 on MacBook Air (M4, 16 GB)
- GLM-5 / GLM-5.1 on MacBook Air (M4, 16 GB)
- GPT-OSS on MacBook Air (M4, 16 GB)
- Granite 3.0 on MacBook Air (M4, 16 GB)
- IBM Granite 4.1 on MacBook Air (M4, 16 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