109B
Parameters
17B
Active (MoE)
512K
Context
58 GB
RAM (Q4_K_M)

RAM by quantization

Lower quantization = less RAM but lower quality. Q4_K_M is the recommended sweet spot for most users.

FormatBitsRAMQualityVerdict
Q3_K_M346 GBModerateTight fit
Q4_K_MREC458 GBGoodNeeds high RAM
Q5_K_M570 GBGoodNeeds high RAM
Q8_08110 GBExcellentMax-spec only

Which Mac can run Llama 4 Scout 17B?

Based on the recommended Q4_K_M quantization. You need RAM for both the model and your running apps — DevPulse calculates this for you. No CUDA installation. No driver hell. Just Apple Silicon doing what Jensen charges $30K for.

8 GB
Can’t run
16 GB
Can’t run
24 GB
Can’t run
32 GB
Can’t run
36 GB
Can’t run
48 GB
Can’t run
64 GB
Close apps first
~6 GB for apps
96 GB
Runs great
~38 GB for apps
128 GB
Runs great
~70 GB for apps
192 GB
Runs great
~134 GB for apps

Tips for running Llama 4 Scout 17B

1 MoE architecture means only 17B params are active per token — fast inference despite 109B total

2 Q3_K_M at 46 GB is the minimum viable option on 64 GB Macs — close everything

3 512K context window is enormous — but longer contexts use more RAM at runtime

4 On 96+ GB Macs, use Q4_K_M for the best quality/memory tradeoff

Related Pages

Run Llama 4 Scout 17B locally. No GPU required.

While cloud GPU prices keep climbing, your Mac can run Llama 4 Scout 17B for free. DevPulse tells you if it fits alongside your dev tools — before you download 58 GB of model weights.

Download for macOS

macOS 14+ · Apple Silicon & Intel · Free during launch