Can Ternary Bonsai 4B run on Mac Studio M3 Ultra 256GB?

YES — Runs great

Q2_0 · 4K context · formula estimate

What this means

Ternary Bonsai 4B fits on the Mac Studio M3 Ultra · 256GB at Q2_0. We estimate it uses 2.2GB of the conservative 248GB working budget.

Estimated decode speed is 372.3–521.2 tokens/s. A roughly 300-word answer may take around 1 seconds.

View technical details ↓Setup guide →

372.3–521.2tokens/s

estimated · instant

2.2GB

needed at Q2_0

Q2_0

quant selected

245.8GB

working headroom

needs 2.2 GBworking budget 248 GB

Apple M3 Ultra256 GB unified memoryMetalActive cooling

See how fast it feels

Using the midpoint of our 372.3–521.2 tokens/s estimate for this demo.

Live demo · 446.8 tokens/s

▌

Compare other speeds →

Where the memory goes

Component	Detail	GB
Model weights	Q2_0 GGUF (1.1 GB) + mmap overhead	1.2
KV cache	4K context window	0.3
Runtime	macOS inference app + compute buffers	0.8
Total needed	Q2_0, 4K context	2.2
Working budget	256 GB unified memory − conservative macOS reserve	248
Headroom	remaining inside the working budget	245.8

Pick your quant

Quant	Download	Memory	Estimated speed	Verdict
Q2_0 ★	1.1 GB	2.2 GB	~372.3–521.2 tok/s	✓ Runs great
Q2_0_g64	1.1 GB	2.2 GB	~372.3–521.2 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=4B ./setup.sh
BONSAI_FAMILY=ternary BONSAI_MODEL=4B 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

Ornith 1.0 397B · IQ4_XS Hunyuan 3 (Hy3) · Q4_K_M Laguna S 2.1 · Q4_K_M Llama 3.3 70B · Q4_K_M Qwen 3.5 35B-A3B · Q4_K_M Qwen 3.6 35B-A3B · Q4_K_M

Ternary Bonsai 4B on other Mac Studio M3 Ultra configurations

Check 96GB

FAQ

Can the Mac Studio M3 Ultra · 256GB run Ternary Bonsai 4B?

Yes at Q2_0. We estimate about 2.2GB of working memory and 372.3–521.2 tokens/s at 4K context.

Which Ternary Bonsai 4B quant should I use on this Mac?

Q2_0. It is a 1.1GB download and leaves about 245.8GB inside our conservative working budget.

Which app should I use for Ternary Bonsai 4B 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 Studio M3 Ultra?

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.