Can Ternary Bonsai 1.7B run on Mac mini M4 32GB?

YES — Runs great

Q2_0 · 4K context · formula estimate

What this means

Ternary Bonsai 1.7B fits on the Mac mini M4 · 32GB at Q2_0. We estimate it uses 1.4GB of the conservative 28.8GB working budget.

Estimated decode speed is 120–168 tokens/s. A roughly 300-word answer may take around 3 seconds.

View technical details ↓Setup guide →

120–168tokens/s

estimated · instant

1.4GB

needed at Q2_0

Q2_0

quant selected

27.4GB

working headroom

needs 1.4 GBworking budget 28.8 GB

Apple M432 GB unified memoryMetalActive cooling

See how fast it feels

Using the midpoint of our 120–168 tokens/s estimate for this demo.

Live demo · 144 tokens/s

▌

Compare other speeds →

Where the memory goes

Component	Detail	GB
Model weights	Q2_0 GGUF (0.5 GB) + mmap overhead	0.5
KV cache	4K context window	0.1
Runtime	macOS inference app + compute buffers	0.8
Total needed	Q2_0, 4K context	1.4
Working budget	32 GB unified memory − conservative macOS reserve	28.8
Headroom	remaining inside the working budget	27.4

Pick your quant

Quant	Download	Memory	Estimated speed	Verdict
Q2_0 ★	0.5 GB	1.4 GB	~120–168 tok/s	✓ Runs great
Q2_0_g64	0.5 GB	1.4 GB	~120–168 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=1.7B ./setup.sh
BONSAI_FAMILY=ternary BONSAI_MODEL=1.7B 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

Qwen 3.5 35B-A3B · Q4_K_M Qwen 3.6 35B-A3B · Q4_K_M Ornith 1.0 35B-A3B · Q4_K_M KAT-Coder V2.5 Dev · Q4_K_M Laguna XS 2.1 · Q4_K_M Qwen3 32B · Q4_K_M

Ternary Bonsai 1.7B on other Mac mini M4 configurations

Check 16GB Check 24GB

FAQ

Can the Mac mini M4 · 32GB run Ternary Bonsai 1.7B?

Yes at Q2_0. We estimate about 1.4GB of working memory and 120–168 tokens/s at 4K context.

Which Ternary Bonsai 1.7B quant should I use on this Mac?

Q2_0. It is a 0.5GB download and leaves about 27.4GB inside our conservative working budget.

Which app should I use for Ternary Bonsai 1.7B 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.