Can I Run Llama 3.3 on Apple M3 Pro?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, comfortably — Llama 3.3 70B Instruct at Q2_K_XS (Tight) needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), leaving ~3.3 GB of the Apple M3 Pro's 27 GB usable memory, at ~4 tok/s (est.).
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Apple M3 Pro Specs
| VRAM | 36 GB unified memory |
| Memory Bandwidth | 153 GB/s |
Llama 3.3 70B Instruct on the Apple M3 Pro: VRAM by quantization
| Quant | VRAM needed | Fits 36 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 143.5 GB | ✗ No | — | — |
| Q8_0 | 77.9 GB | ✗ No | — | — |
| Q6_K | 60.9 GB | ✗ No | — | — |
| Q5_K_M | 53.1 GB | ✗ No | — | — |
| Q4_K_M | 45.7 GB | ✗ No | — | — |
| Q3_K_M | 33.3 GB | ✗ No | — | — |
| Q2_K | 26.5 GB | ✓ Yes | 8K | — |
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 36 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 Q2_K_XS (Tight) on the Apple M3 Pro: 8K 23.7 GB · 32K 31.7 GB ✗ · 128K 64 GB ✗. Past 32K it no longer fits 36 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Llama 3.3 70B Instruct on 256 GB of system RAM, CPU only: runs, but too slowly to be worth it.
Llama 3.3 Sizes That Fit the Apple M3 Pro (at 8K context)
| Llama 3.3 70B Instruct | Q2_K_XS (Tight) · 23.7 GB at 8K context · ~4 tok/s (est.) |
Llama 3.3 needs ~24 GB but this GPU has 36 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Can I run Llama 3.3 on the Apple M3 Pro?
Yes, comfortably — Llama 3.3 70B Instruct at Q2_K_XS (Tight) needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), leaving ~3.3 GB of the Apple M3 Pro's 27 GB usable memory, at ~4 tok/s (est.).
What's the best Llama 3.3 size for the Apple M3 Pro?
Llama 3.3 70B Instruct at Q2_K_XS (Tight) quantization needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), estimated ~4 tokens/sec.
Llama 3.3 on Other GPUs
- Llama 3.3 on NVIDIA GeForce RTX 5090
- Llama 3.3 on Apple M4
- Llama 3.3 on Apple M2 Pro
- Llama 3.3 on Apple M1 Pro
- Llama 3.3 on Apple M5
Popular Models on the Apple M3 Pro
VRAM Tier
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