Can I Run Granite 3.0 on MacBook Air (M4, 16 GB)?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 21 października 2024

Yes

Yes — Granite 3.0 8B Instruct at Q8_0 needs about 10.6 GB of the 12 GB usable on MacBook Air (M4, 16 GB) (~1.4 GB spare), at ~7 tok/s (estimated), with room for about 16,384 tokens of context.

Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~7 tok/s

See what else this hardware can run →

Kup ten sprzęt Apple MacBook Air 13-inch (M5, 16 GB) — 16 GB unified memory · 153 GB/sUruchom w chmurze RTX 4090 w RunPod — od $0.34/godz. · stawka sprawdzona 2026-07

lub porównaj w Vast.ai od $0.35/godz. (typical low · varies)

Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.

MacBook Air (M4, 16 GB) — what it gives a model

Usable memory for models12 GB
Memory bandwidth120 GB/s
Form factorLaptop
Operating systemmacOS
Memory upgradeableNo — soldered

Granite 3.0 on MacBook Air (M4, 16 GB): memory by quantization

QuantMemory neededFits 12 GB?Max contextEst. speedDownload
F1618.1 GB✗ No——16 GB
Q8_010.6 GB✓ Yes16K~7 tok/s8.5 GB
Q6_K8.7 GB✓ Yes16K~8.9 tok/s6.6 GB
Q5_K_M7.8 GB✓ Yes32K~10.1 tok/s5.7 GB
Q4_K_M7 GB✓ Yes32K~11.5 tok/s4.8 GB
Q3_K_M5.6 GB✓ Yes32K~15.4 tok/s3.4 GB
Q2_K4.8 GB✓ Yes32K~18.8 tok/s2.6 GB
Superseded model. Granite 3.0 has been superseded by IBM Granite 4.0. This page is kept for reference; the newer family is a better starting point. IBM Granite 4.0 needs at least 22 GB at Q4_K_M with an 8K context, so it does not fit the MacBook Air (M4, 16 GB).

What to watch out for

MacBook Air M4 16 GB limitations

Recommended setup

Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput

How these numbers are calculated

FAQ

Can I run Granite 3.0 on MacBook Air (M4, 16 GB)?

Yes — Granite 3.0 8B Instruct at Q8_0 needs about 10.6 GB of the 12 GB usable on MacBook Air (M4, 16 GB) (~1.4 GB spare), at ~7 tok/s (estimated), with room for about 16,384 tokens of context.

Which quantization of Granite 3.0 should I use on MacBook Air (M4, 16 GB)?

Q8_0 — it needs about 10.6 GB of the 12 GB available, downloads as roughly 8.5 GB, and runs at an estimated 7 tokens/sec with up to 16K of context.

What limits Granite 3.0 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)

Granite 3.0 on GPUs

What This Model Is Good At

Model & Tools

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