Can Fara 1.5 9B run on Mac mini M6 16GB?
What this means
Fara 1.5 9B fits on the Mac mini M6 · 16GB at Q4_K_M. We estimate it uses 7.7GB of the conservative 13GB working budget.
Estimated decode speed is 14.4–20.2 tokens/s. A roughly 300-word answer may take around 23 seconds.
See how fast it feels
Using the midpoint of our 14.4–20.2 tokens/s estimate for this demo.
Where the memory goes
| Component | Detail | GB |
|---|---|---|
| Model weights | Q4_K_M GGUF (5.9 GB) + mmap overhead | 6.2 |
| KV cache | 4K context window | 0.7 |
| Runtime | macOS inference app + compute buffers | 0.8 |
| Total needed | at Q4_K_M, 4K context | 7.7 |
| Working budget | 16 GB unified memory − conservative macOS reserve | 13 |
| Headroom | remaining inside the working budget | 5.3 |
Pick your quant
| Quant | Download | Memory | Estimated speed | Verdict |
|---|---|---|---|---|
| Q2_K | 4.1 GB | 5.8 GB | ~20.7–29 tok/s | ✓ Runs great |
| Q3_K_M | 4.9 GB | 6.6 GB | ~17.3–24.3 tok/s | ✓ Runs great |
| IQ4_XS | 5.2 GB | 6.9 GB | ~16.3–22.9 tok/s | ✓ Runs great |
| Q4_0 | 5.5 GB | 7.2 GB | ~15.5–21.6 tok/s | ✓ Runs great |
| Q4_K_S | 5.6 GB | 7.3 GB | ~15.2–21.3 tok/s | ✓ Runs great |
| Q4_K_M ★ | 5.9 GB | 7.7 GB | ~14.4–20.2 tok/s | ✓ Runs great |
| Q5_K_M | 6.9 GB | 8.7 GB | ~12.3–17.2 tok/s | ✓ Runs great |
| Q6_K | 7.7 GB | 9.5 GB | ~11–15.5 tok/s | ✓ Runs great |
| Q8_0 | 9.5 GB | 11.4 GB | ~8.9–12.5 tok/s | ✓ Runs great |
Use this model for its intended task
Fara 1.5 9B is designed to operate websites from screenshots as a computer-use agent. This Mac has enough working memory for the tracked Q4_K_M weights, but loading the file in a plain chat window does not supply the inputs, tools, or action loop that make the model useful.
It documents the intended workflow and supported developer runtimes. This is not yet a point-and-click setup for beginners, so do not install LM Studio expecting an ordinary chat tutorial to reproduce the model's task.
Choose Llama 3.2 3B instead. Its page gives the complete graphical install, download, first prompt, and offline check.
This model is designed to operate websites from screenshots as a computer-use agent. Its weights may fit in memory, but it needs a browser-control harness that repeatedly supplies screenshots and executes the model's actions. A normal LM Studio chat does not provide that workflow.
Other models on this Mac
Fara 1.5 9B on other Mac mini M6 configurations
FAQ
Can the Mac mini M6 · 16GB run Fara 1.5 9B?
Yes at Q4_K_M. We estimate about 7.7GB of working memory and 14.4–20.2 tokens/s at 4K context.
Which Fara 1.5 9B quant should I use on this Mac?
Q4_K_M. It is a 5.9GB download and leaves about 5.3GB inside our conservative working budget.
Which app should I use for Fara 1.5 9B on this Mac?
Fara 1.5 9B is a task-specific model, not a normal local chat download. The selected weights fit this Mac, but the model still needs its publisher's intended workflow. This page links that repository and recommends Llama 3.2 3B if you just want local chat.
Are these speeds measured on a Mac mini M6?
No. The range is a formula estimate based on memory bandwidth, model size, active parameters, cooling, and a 4K context. The app, backend, thermals, and prompt can change real performance.