Model × hardware check
Can Bonsai 2 run on Mac mini M5 Pro · 48 GB?
Yes, this is a comfortable estimate at 8,192 tokens. a true ternary 27B model whose packed files are smaller than many 7-9B Q4 builds The current Mac mini M5 Pro combines 48 GB of unified memory with 307 GB/s of memory bandwidth in a compact chassis.
Short answer
Comfortable fit
At least 20% memory headroom remains after weights, KV cache, and runtime overhead.
- Available unified memory
- 48 GB
- Estimated requirement
- 9.2 GB
- Headroom
- +38.8 GB
- Fit ratio
- 519%
- Recommended quantization
- PQ2_0
- Context ceiling
- 262,144 tokens
- Speed estimate
- Estimate · Slow relative band
What the numbers say
The selected Bonsai 2 package uses 7.2 GB of weight files. The 8K KV cache estimate is 0.5 GB, and the formula adds 1.5 GB of runtime overhead. That produces a 9.2 GB requirement against 48 GB of unified memory.
Current-generation Mac mini with M5 Pro and 307 GB/s memory bandwidth. The 64 GB configuration requires the 20-core GPU bin. Unified memory is shared by the CPU, GPU, operating system, and applications.
The context ceiling shown above is the point where the same formula reaches the machine's capacity. It is not a promise that the backend can allocate that full context after the operating system and other applications take their share.
Quantization trade-offs at 8K
| Quantization | Weight files | Bits / weight | 8K requirement | Fit on this machine | Context ceiling | Speed estimate | Ollama |
|---|---|---|---|---|---|---|---|
| PTQ1_0 | 5.95 GB | 1.75 | 8.0 GB | Comfortable fit · 601% | 262,144 tokens | Estimate · Slow relative band | No verified tag |
| PQ2_0 | 7.21 GB | 2.13 | 9.2 GB | Comfortable fit · 519% | 262,144 tokens | Estimate · Slow relative band | No verified tag |
| Q2_0 | 7.63 GB | 2.25 | 9.7 GB | Comfortable fit · 497% | 262,144 tokens | Estimate · Slow relative band | ollama run bonsai-2:27b-q2_0 |
This model uses true ternary language weights at roughly 1.75-2.25 bits per weight after scales and metadata. The table uses each published GGUF size directly; it does not replace Bonsai's ternary file with a generic Q4 estimate.
Run commands
llama-cli -hf prism-ml/Ternary-Bonsai-2-27B-gguf --hf-file Ternary-Bonsai-2-27B-PQ2_0.gguf -c 8192 -ngl 99 -p "Your prompt"mlx_lm.generate --model prism-ml/Ternary-Bonsai-2-27B-mlx-2bit --prompt "Your prompt" --max-tokens 8192Commands are examples, not a guarantee that the selected quantization tag is available in every runtime. Confirm the package name and license on the linked model page.
If it does not fit
This pairing already clears the comfort threshold
The current estimate leaves +38.8 GB. A longer context or another GPU application can reduce that margin, so verify free memory before relying on it.
Low-cost setup upgrades
Useful upgrades around Mac mini M5 Pro · 48 GB
These are optional setup improvements, not a claim that an accessory can increase GPU or unified-memory capacity.
Mac mini dock or stand with an NVMe slot
Adds storage and front-facing ports without buying a larger internal drive. Verify the Mac model, Thunderbolt version, and power-delivery limits before ordering.
Search current listings on AmazonExternal NVMe SSD for model storage
Keeps large GGUF and MLX files off the boot drive. Fast storage reduces load time, but it does not increase the memory available for inference.
Search current listings on AmazonThunderbolt or USB4 NVMe enclosure
A reusable enclosure lets you choose the drive capacity separately. Confirm the host supports the advertised Thunderbolt or USB4 generation.
Search current listings on AmazonAs an Amazon Associate I earn from qualifying purchases. Links are sponsored search links and do not change the price you pay. Affiliate disclosure.
Where this estimate can break
- PTQ1_0 and PQ2_0 require Prism ML's llama.cpp fork. Q2_0 runs in stock llama.cpp b11556 or newer; older builds can load it without warning and produce garbage.
- The calculator models the 27B flagship. The 2B, 4B, and 9B variants are listed separately on this page and use their own files and vision towers.
- The vision tower is optional for text inference but adds about 0.63 GB when image input is enabled.
- The 262K context remains impractical on an 8-12 GB machine even though the ternary weights themselves are unusually small.
- Other GPU applications, display buffers, and the operating system reduce usable memory.
- Longer prompts, concurrent requests, and a different backend can raise peak memory.
Compare this pairing
FAQ
Questions about this pairing.
How much memory does Bonsai 2 need on Mac mini M5 Pro · 48 GB?
At an 8K context with PQ2_0, the estimate is 9.2 GB: 7.2 GB of weights, 0.5 GB of KV cache, and 1.5 GB of runtime overhead. The available unified memory is 48 GB.
What context length can Mac mini M5 Pro · 48 GB handle with this model?
The calculated ceiling is 262,144 tokens for this quantization, capped by the model's native 262,144-token context. Actual usable context can be lower after the OS, other applications, and backend workspace.
How does quantization change the memory requirement on Mac mini M5 Pro · 48 GB?
At 8,192 tokens, the published variants calculate as follows: PTQ1_0: 8.0 GB, comfortable fit; PQ2_0: 9.2 GB, comfortable fit; Q2_0: 9.7 GB, comfortable fit. A lower-bit file can move a result from too large to tight, but quality and kernel support may differ.
What can I run if Bonsai 2 does not fit on Mac mini M5 Pro · 48 GB?
This selection already clears the comfort threshold. If you later increase the context, monitor the ceiling of 262,144 tokens; smaller alternatives include Flint 40B, NVIDIA Nemotron 3.5 Bolt E4B, LFM3-1.7B.
Is the speed estimate for Bonsai 2 on Mac mini M5 Pro · 48 GB measured?
No. Slow relative band is a heuristic band derived from 27.36B active parameters and 307 GB/s published memory bandwidth. Backend kernels, batch size, thermals, and CPU offload can change actual tokens per second.