Can I Run Llama 3.2 Vision on MacBook Air (M4, 16 GB)?
Superseded model. Llama 3.2 Vision has been superseded by Llama 4. This page is kept for reference; the newer family is a better starting point.
View Llama 4 →
Written by Jakub Rusinowski · Last updated September 25, 2024
Yes
Yes — Llama 3.2 Vision 11B at Q6_K needs about 10.8 GB of the 12 GB usable on MacBook Air (M4, 16 GB) (~1.2 GB spare), at ~6.9 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: high · Recommended quantization: Q6_K · Estimated speed: ~6.9 tok/s
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 |
Llama 3.2 Vision on MacBook Air (M4, 16 GB): memory by quantization
| Quant | Memory needed | Fits 12 GB? | Max context | Est. speed | Download |
|---|
| F16 | 23.3 GB | ✗ No | — | — | 21.2 GB |
| Q8_0 | 13.4 GB | ✗ No | — | — | 11.3 GB |
| Q6_K | 10.8 GB | ✓ Yes | 8K | ~6.9 tok/s | 8.7 GB |
| Q5_K_M | 9.7 GB | ✓ Yes | 16K | ~7.8 tok/s | 7.5 GB |
| Q4_K_M | 8.5 GB | ✓ Yes | 16K | ~9 tok/s | 6.4 GB |
| Q3_K_M | 6.7 GB | ✓ Yes | 32K | ~12.2 tok/s | 4.5 GB |
| Q2_K | 5.6 GB | ✓ Yes | 32K | ~15.1 tok/s | 3.5 GB |
Which Llama 3.2 Vision sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| Llama 3.2 Vision 90B | 57.8 GB | ✗ Too large | — |
| Llama 3.2 Vision 11B | 8.5 GB | ✓ Fits | ~9 tok/s |
What to watch out for
- Only ~1.2 GB of headroom at Q6_K: a longer context or a second application can push this into swapping.
- 1 larger variant of Llama 3.2 Vision does 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 Llama 3.2 Vision on MacBook Air (M4, 16 GB)?
Yes — Llama 3.2 Vision 11B at Q6_K needs about 10.8 GB of the 12 GB usable on MacBook Air (M4, 16 GB) (~1.2 GB spare), at ~6.9 tok/s (estimated), with room for about 8,192 tokens of context.
Which quantization of Llama 3.2 Vision should I use on MacBook Air (M4, 16 GB)?
Q6_K — it needs about 10.8 GB of the 12 GB available, downloads as roughly 8.7 GB, and runs at an estimated 6.9 tokens/sec with up to 8K of context.
What limits Llama 3.2 Vision 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
Other Models on MacBook Air (M4, 16 GB)
Llama 3.2 Vision on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | Llama 3.2 Vision model page | Check your hardware