LLM Roofline
Apple · UMA · Backend: mlx

Apple Mac Mini M4 Pro (64 GB) — LLM Sizing & Speed Matrix

64 GB UMA fits 70B Q4_K_M when wired limit is tuned via sysctl; ~5-6 tok/s on 70B dense.

Reference Pricing
$1,999 Street
Usable Memory
49.92 GiB (56.32 tuned)
Memory Bandwidth
273 GB/s (74% eff.)
FP16 Compute
18.4 TFLOPS
Roofline Ridge
52.8 FLOP/B
Power (Load / Idle)
95W / 8W

All 32 Open-Weight Models on Apple Mac Mini M4 Pro (64 GB) (Q4_K_M @ 32k)

Model Status Weights Total @ 32k Decode TTFT (4k) Max Safe Ctx
Llama-3.3 Nemotron Super 49B COMFORTABLE 28.7 GiB 36.5 GiB 5.4 tok/s 39.60s 128k
Mixtral 8x7B Instruct COMFORTABLE 26.9 GiB 32.0 GiB 14.5 tok/s 10.35s 32k
Qwen3 32B COMFORTABLE 18.9 GiB 28.1 GiB 7.0 tok/s 26.86s 40k
Qwen2.5 Coder 32B COMFORTABLE 18.9 GiB 28.1 GiB 7.0 tok/s 26.24s 32k
DeepSeek-R1 Distill Qwen 32B COMFORTABLE 18.9 GiB 28.1 GiB 7.0 tok/s 26.24s 128k
QwQ 32B Reasoning COMFORTABLE 18.9 GiB 28.1 GiB 7.0 tok/s 26.24s 40k
GLM-4 32B 0414 COMFORTABLE 18.6 GiB 21.9 GiB 9.2 tok/s 26.01s 32k
Qwen3 30B-A3B COMFORTABLE 17.6 GiB 21.4 GiB 33.8 tok/s 3.19s 40k
Gemma 3 27B IT COMFORTABLE 15.8 GiB 20.0 GiB 10.1 tok/s 21.87s 128k
Mistral Small 3.1 24B COMFORTABLE 13.8 GiB 20.1 GiB 10.0 tok/s 18.97s 128k
Codestral 22B COMFORTABLE 12.8 GiB 21.2 GiB 9.5 tok/s 18.16s 32k
Qwen3 14B COMFORTABLE 8.5 GiB 14.8 GiB 13.9 tok/s 12.04s 40k
Qwen2.5 14B Instruct COMFORTABLE 8.5 GiB 15.8 GiB 12.9 tok/s 12.17s 32k
DeepSeek-R1 Distill Qwen 14B COMFORTABLE 8.5 GiB 15.8 GiB 12.9 tok/s 12.17s 128k
Phi-4 14B COMFORTABLE 8.5 GiB 12.8 GiB 16.2 tok/s 11.96s 16k
Gemma 3 12B IT COMFORTABLE 7.0 GiB 10.4 GiB 20.1 tok/s 10.02s 128k
Qwen3 8B COMFORTABLE 4.7 GiB 10.3 GiB 20.4 tok/s 6.79s 40k
Llama 3.1 8B Instruct COMFORTABLE 4.6 GiB 9.7 GiB 21.8 tok/s 6.61s 128k
Qwen2.5 7B Instruct COMFORTABLE 4.4 GiB 7.2 GiB 30.7 tok/s 6.18s 32k
Gemma 3 4B IT COMFORTABLE 2.5 GiB 4.2 GiB 56.4 tok/s 3.56s 128k
Qwen2.5 72B Instruct TUNABLE_UMA 41.9 GiB 53.5 GiB 3.6 tok/s 57.90s 32k
DeepSeek-R1 Distill Llama 70B TUNABLE_UMA 40.7 GiB 52.3 GiB 3.7 tok/s 56.29s 45k
Llama 3.3 70B Instruct TUNABLE_UMA 40.7 GiB 52.3 GiB 3.7 tok/s 56.29s 45k
Llama 3.1 70B Instruct TUNABLE_UMA 40.7 GiB 52.3 GiB 3.7 tok/s 56.29s 45k
DeepSeek-R1 671B OOM 386.4 GiB 390.1 GiB OOM — OOM
DeepSeek-V3 671B OOM 386.4 GiB 390.1 GiB OOM — OOM
Llama 3.1 405B Instruct OOM 233.8 GiB 252.3 GiB OOM — OOM
Llama 4 Maverick 400B-A17B OOM 231.5 GiB 238.8 GiB OOM — OOM
Qwen3 235B-A22B OOM 135.4 GiB 142.4 GiB OOM — OOM
Mixtral 8x22B Instruct OOM 81.2 GiB 89.6 GiB OOM — OOM
Command A 111B OOM 63.9 GiB 68.9 GiB OOM — OOM
Llama 4 Scout 109B-A17B OOM 62.8 GiB 70.0 GiB OOM — OOM

Interactive Apple Mac Mini M4 Pro (64 GB) Simulator

49.9B Dense · GQA
273 GB/s · 18.4 TFLOPS
3. Weight Quantization 4.85 bpw
4. KV Cache
32,768 tok
Compute Roofline
COMFORTABLE FIT Memory-Bandwidth Bound
Max Safe Ctx: 102k (128k tuned)
Memory Allocation Footprint 36.54 / 49.92 GiB usable
Weights: 28.74 GiB KV Cache: 6.13 GiB Overhead: 1.68 GiB Headroom: 13.38 GiB
Decode Speed
5.4
tok/s (batch=1)
Prefill Speed
104
prompt tok/s
TTFT Latency
39.60s
for 4,096 tok
Active Params
49.9B
of 49.9B total
llama.cpp Server Command
llama-server -hf nvidia/Llama-3_3-Nemotron-Super-49B-v1:Q4_K_M -ngl 99 -fa on -c 32768 --port 8080
Context KV Cache Total VRAM Decode Status
4k 0.77 GiB 30.62 GiB 6.4 tok/s COMFORTABLE
8k 1.53 GiB 31.94 GiB 6.2 tok/s COMFORTABLE
16k 3.06 GiB 33.48 GiB 5.9 tok/s COMFORTABLE
32k 6.13 GiB 36.54 GiB 5.4 tok/s COMFORTABLE
64k 12.25 GiB 42.66 GiB 4.6 tok/s COMFORTABLE
128k 24.50 GiB 54.91 GiB 3.5 tok/s TUNABLE_UMA

Buy-vs-Cloud-vs-API Monthly TCO Break-Even

USE SERVERLESS API
Own Hardware/mo
$48.58
905.8h active + power
Cloud GPU/mo
$927.06
@$0.89/hr spot/pod
Serverless API/mo
$13.50
Payback: 1277.6 mo

Hardware FAQ — Apple Mac Mini M4 Pro (64 GB)

How much usable VRAM / GPU memory does Apple Mac Mini M4 Pro (64 GB) actually provide for LLMs?

Out of the box, Apple Mac Mini M4 Pro (64 GB) safely reserves 49.92 GiB for GPU inference, expandable up to 56.32 GiB with OS UMA tuning.

What is the largest Q4_K_M model Apple Mac Mini M4 Pro (64 GB) can run at 32k context?

With Q4_K_M weights and FP16 KV cache at 32k context, the largest fitting model in our verified catalog on Apple Mac Mini M4 Pro (64 GB) is Llama-3.3 Nemotron Super 49B (49.9B total).