baichuan inc Baichuan M2 32B needs ~51.8 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~29 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
28.5 tok/s
TTFT
6786 ms
Safe context
581K
Memory
51.8 GB / 184.3 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 28.5 tok/s | 3701 ms | 581K |
| Coding | C | Runs well | 28.5 tok/s | 6786 ms | 581K |
| Agentic Coding | C | Runs well | 28.5 tok/s | 9870 ms | 581K |
| Reasoning | C | Runs well | 28.5 tok/s | 8019 ms | 581K |
| RAG | C | Runs well | 28.5 tok/s | 12338 ms | 581K |
How baichuan inc Baichuan M2 32B (32B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | D37 |
Q3_K_S | 3 | 15.7 GB | Low | D37 |
NVFP4 | 4 |
Copy-paste commands to run baichuan inc Baichuan M2 32B on your machine.
Run
lms load hf-bartowski--baichuan-inc-baichuan-m2-32b-gguf && lms server startUpgrade options
Raises estimated decode speed by about 950%.
Adds memory headroom for longer context windows and future model growth.
~$8,000 MSRP
Raises estimated decode speed by about 643%.
~$15,000 MSRP
Yes, Mac Studio M3 Ultra 256GB can run baichuan inc Baichuan M2 32B with a C grade (Runs well). Expected decode speed: 28.5 tok/s.
baichuan inc Baichuan M2 32B (32B parameters) requires approximately 51.8 GB of memory with Q4_K_M quantization.
The recommended quantization for baichuan inc Baichuan M2 32B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M3 Ultra 256GB, baichuan inc Baichuan M2 32B achieves approximately 28.5 tokens per second decode speed with a time-to-first-token of 6786ms using Q4_K_M quantization.
For coding workloads, baichuan inc Baichuan M2 32B on Mac Studio M3 Ultra 256GB receives a C grade with 28.5 tok/s and 581K context.
On Mac Studio M3 Ultra 256GB, baichuan inc Baichuan M2 32B can safely use up to 581K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-bartowski--baichuan-inc-baichuan-m2-32b-gguf-on-m3-ultra-256gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
17.9 GB |
| Medium |
| D37 |
Q4_K_M | 4 | 19.5 GB | Medium | D37 |
Q5_K_M | 5 | 23.0 GB | High | D38 |
Q6_K | 6 | 26.2 GB | High | D38 |
Q8_0 | 8 | 34.2 GB | Very High | D39 |
F16Best for your GPU | 16 | 65.6 GB | Maximum | C43 |
Not always. Mac Studio M3 Ultra 256GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.