Can I Run Llama 3.2 Family on Apple M5 Max?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 września 2026

Yes, comfortably — Llama 3.2 90B Vision Instruct at Q4_K_M needs 57.8 GB at 8K context (53.6 GB weights + 4.2 GB KV cache/overhead), leaving ~38.2 GB of the Apple M5 Max's 96 GB usable memory, at ~6 tok/s (est.), with room for up to 64K context.

See what else this hardware can run →

Kup ten sprzęt Apple MacBook Pro M5 Max — 128 GB unified memory · 614 GB/sUruchom w chmurze NVIDIA A100 80GB w RunPod — od $1.39/godz. · stawka sprawdzona 2026-07

lub porównaj w Vast.ai od $0.77/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.

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.

Apple MacBook Pro M5 Max
128 GB unified memory · 614 GB/s
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

Apple M5 Max Specs

VRAM128 GB unified memory
Memory Bandwidth614 GB/s

Llama 3.2 90B Vision Instruct on the Apple M5 Max: VRAM by quantization

QuantVRAM neededFits 128 GB?Max contextWhole PC
F16181.8 GB✗ No——
Q8_098.5 GB✗ No——
Q6_K77 GB✓ Yes32K—
Q5_K_M67.1 GB✓ Yes64K—
Q4_K_M57.8 GB✓ Yes64K—
Q3_K_M42 GB✓ Yes64K—
Q2_K33.3 GB✓ Yes64K—

Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 128 GB of unified memory. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.

Context costs VRAM too. At Q4_K_M on the Apple M5 Max: 8K 57.8 GB · 32K 67.8 GB · 125K 106.8 GB ✗. Past 125K it no longer fits 128 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.

No compatible GPU? Llama 3.2 Family on 8 GB of system RAM, CPU only: runs.

Llama 3.2 Family Sizes That Fit the Apple M5 Max (at 8K context)

Llama 3.2 90B Vision InstructQ4_K_M · 57.8 GB at 8K context · ~6 tok/s (est.)
Llama 3.2 11B Vision InstructQ4_K_M · 8.5 GB at 8K context · ~42 tok/s (est.)
Llama 3.2 3B InstructQ4_K_M · 3.7 GB at 8K context · ~98 tok/s (est.)
Llama 3.2 1B InstructQ4_K_M · 1.8 GB at 8K context · ~178 tok/s (est.)
Won't fit — rent Llama 3.2 Family instead

Llama 3.2 Family needs ~58 GB but this GPU has 128 GB. Rent a A100 (80 GB)-class GPU by the hour instead of buying one:

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Vast.ai $0.77/hr · typical low · varies
Rent on Vast.ai →
RunPod $1.39/hr
Rent on RunPod →

Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.

FAQ

Is the Apple M5 Max enough to run Llama 3.2 Family locally?

Yes, comfortably — Llama 3.2 90B Vision Instruct at Q4_K_M needs 57.8 GB at 8K context (53.6 GB weights + 4.2 GB KV cache/overhead), leaving ~38.2 GB of the Apple M5 Max's 96 GB usable memory, at ~6 tok/s (est.), with room for up to 64K context.

What's the best Llama 3.2 Family size for the Apple M5 Max?

Llama 3.2 90B Vision Instruct at Q4_K_M quantization needs 57.8 GB at 8K context (53.6 GB weights + 4.2 GB KV cache/overhead), estimated ~6 tokens/sec, up to 64K context.

Every Llama 3.2 Family size on the Apple M5 Max

SizeVRAM at 8KVerdictSpeed
Llama 3.2 90B Vision Instruct57.8 GBRuns~6 tok/s
Llama 3.2 11B Vision Instruct8.5 GBRuns~42 tok/s
Llama 3.2 3B Instruct3.7 GBRuns~98 tok/s
Llama 3.2 1B Instruct1.8 GBRuns~178 tok/s

Llama 3.2 Family on Other GPUs

Popular Models on the Apple M5 Max

VRAM Tier

Troubleshooting

Buying Guide

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