Can Ternary Bonsai 8B run on Mac mini M4 16GB?

YES — Runs great

Q2_0 · 4K context · formula estimate

What this means

Ternary Bonsai 8B fits on the Mac mini M4 · 16GB at Q2_0. We estimate it uses 3.7GB of the conservative 13GB working budget.

Estimated decode speed is 27.3–38.2 tokens/s. A roughly 300-word answer may take around 12 seconds.

View technical details ↓Setup guide →

27.3–38.2tokens/s

estimated · instant

3.7GB

needed at Q2_0

Q2_0

quant selected

9.3GB

working headroom

needs 3.7 GBworking budget 13 GB

Apple M416 GB unified memoryMetalActive cooling

See how fast it feels

Using the midpoint of our 27.3–38.2 tokens/s estimate for this demo.

Live demo · 32.8 tokens/s

▌

Compare other speeds →

Where the memory goes

Component	Detail	GB
Model weights	Q2_0 GGUF (2.2 GB) + mmap overhead	2.3
KV cache	4K context window	0.6
Runtime	macOS inference app + compute buffers	0.8
Total needed	Q2_0, 4K context	3.7
Working budget	16 GB unified memory − conservative macOS reserve	13
Headroom	remaining inside the working budget	9.3

Pick your quant

Quant	Download	Memory	Estimated speed	Verdict
Q2_0 ★	2.2 GB	3.7 GB	~27.3–38.2 tok/s	✓ Runs great
Q2_0_g64	2.3 GB	3.8 GB	~26.1–36.5 tok/s	✓ Runs great

Get it running on this Mac

Choose the beginner-friendly build instead.

This Mac has enough memory, but the tracked Q2_0 ternary file is not supported by the current point-and-click apps. For a first local chat, use Bonsai 27B 1-bit in Locally AI. Do not download PQ2_0; the publisher marks it unsupported.

Only use the publisher tool if you are comfortable with Terminal.

The advanced path is complete below, but it is not required for ordinary local AI.

Advanced publisher setup (Terminal)

Install Apple's command-line tools if macOS asks, then run:

git clone https://github.com/PrismML-Eng/Bonsai-demo.git
cd Bonsai-demo
BONSAI_OPENWEBUI=0 BONSAI_SKIP_MLX=1 BONSAI_FAMILY=ternary BONSAI_MODEL=8B ./setup.sh
BONSAI_FAMILY=ternary BONSAI_MODEL=8B BONSAI_CTX=4096 ./scripts/start_llama_server.sh

When the server says it is ready, open http://localhost:8080. Start with 4K context. This route uses the publisher's Prism runtime, not Jan or LM Studio.

Other models on this Mac

Bonsai 27B (1-bit) · Q1_0 Ternary Bonsai 27B · Q2_0 Qwen3 14B · Q4_K_M Phi-4 14B · Q4_K_M Ministral 3 14B · Q4_K_M Gemma 3 12B · Q4_K_M

Ternary Bonsai 8B on other Mac mini M4 configurations

Check 24GB Check 32GB

FAQ

Can the Mac mini M4 · 16GB run Ternary Bonsai 8B?

Yes at Q2_0. We estimate about 3.7GB of working memory and 27.3–38.2 tokens/s at 4K context.

Which Ternary Bonsai 8B quant should I use on this Mac?

Q2_0. It is a 2.2GB download and leaves about 9.3GB inside our conservative working budget.

Which app should I use for Ternary Bonsai 8B on this Mac?

Current beginner Mac apps do not load this exact file. Use Bonsai 27B 1-bit in Locally AI instead, or open the advanced publisher instructions on this page.

Are these speeds measured on a Mac mini M4?

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.