1.1B
Parameters
2K
Context
0.8 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
Q4_K_MREC40.8 GBGoodRuns great
Q8_081.2 GBExcellentRuns great
F16162.2 GBLosslessRuns great

Which Mac can run TinyLlama 1.1B?

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
Close apps first
~7 GB for apps
16 GB
Runs well
~15 GB for apps
24 GB
Runs great
~23 GB for apps
32 GB
Runs great
~31 GB for apps
36 GB
Runs great
~35 GB for apps
48 GB
Runs great
~47 GB for apps
64 GB
Runs great
~63 GB for apps
96 GB
Runs great
~95 GB for apps
128 GB
Runs great
~127 GB for apps
192 GB
Runs great
~191 GB for apps

Tips for running TinyLlama 1.1B

1 Perfect for testing your local AI setup before committing to larger models

2 Runs comfortably alongside Chrome, VS Code, and Docker on 8 GB Macs

3 Use Q4_K_M quantization — quality is nearly identical to F16 at this size

Related Pages

Run TinyLlama 1.1B locally. No GPU required.

While cloud GPU prices keep climbing, your Mac can run TinyLlama 1.1B for free. DevPulse tells you if it fits alongside your dev tools — before you download 0.8 GB of model weights.

Download for macOS

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