Can I Run Llama 3.3 on Apple M4 Pro?
Written by Jakub Rusinowski · Last updated July 12, 2026
Only with offload — 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) against the Apple M4 Pro's 18 GB usable memory, so part of it spills onto CPU/system RAM and speed drops sharply.
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Apple M4 Pro Specs
| VRAM | 24 GB unified memory |
| Memory Bandwidth | 273 GB/s |
Llama 3.3 70B Instruct on the Apple M4 Pro: VRAM by quantization
| Quant | VRAM needed | Fits 24 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 | ✗ No | — | — |
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 24 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 M4 Pro: 8K 23.7 GB ✗ · 32K 31.7 GB ✗ · 128K 64 GB ✗. Past 8K it no longer fits 24 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.
Why It Does Not Fit
Every Llama 3.3 variant requires more VRAM than the Apple M4 Pro provides (24 GB).
Nearest GPU That Fits
Intel Arc Pro B70 (32 GB VRAM).
Llama 3.3 needs ~24 GB but this GPU has 24 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
Llama 3.3 on the Apple M4 Pro — does it fit?
Only with offload — 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) against the Apple M4 Pro's 18 GB usable memory, so part of it spills onto CPU/system RAM and speed drops sharply.
What GPU should I get instead to run Llama 3.3?
The Intel Arc Pro B70 (32 GB VRAM) is the cheapest upgrade that fits it.
Llama 3.3 on Other GPUs
- Llama 3.3 on NVIDIA GeForce RTX 4090
- Llama 3.3 on NVIDIA GeForce RTX 3090
- Llama 3.3 on AMD Radeon RX 7900 XTX
- Llama 3.3 on Apple M3
- Llama 3.3 on Apple M2
VRAM Tier
Troubleshooting
- Ollama: "model requires more system memory than is available"
- Out of memory at long context (the KV cache, not the weights)
Buying Guide
← Can I Run It? | Llama 3.3 Model Page | Apple M4 Pro GPU Page | VRAM calculator | Check Your Hardware