MacBook Pro M4 Pro 64GBBudget pick
64 GB Unified (+16)
C
Adds memory headroom for longer context windows and future model growth.19.4 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
baichuan inc Baichuan M2 32B needs ~29.4 GB VRAM. MacBook Pro M4 Pro 48GB has 34.6 GB. With Q4_K_M quantization, expect ~19 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
Tight fit
Decode
19.4 tok/s
TTFT
9988 ms
Safe context
38K
Memory
29.4 GB / 34.6 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 | 19.4 tok/s | 5448 ms | 38K |
| Coding | C | Tight fit | 19.4 tok/s | 9988 ms | 38K |
| Agentic Coding | C | Runs with offload | 19.4 tok/s | 14527 ms | 38K |
| Reasoning | C | Tight fit | 19.4 tok/s | 11803 ms | 38K |
| RAG | C | Runs with offload | 19.4 tok/s | 18159 ms | 38K |
How baichuan inc Baichuan M2 32B (32B params) fits at each quantization level on MacBook Pro M4 Pro 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | C46 |
Q3_K_S | 3 | 15.7 GB | Low | C48 |
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
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Yes, MacBook Pro M4 Pro 48GB can run baichuan inc Baichuan M2 32B with a C grade (Tight fit). Expected decode speed: 19.4 tok/s.
baichuan inc Baichuan M2 32B (32B parameters) requires approximately 29.4 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 MacBook Pro M4 Pro 48GB, baichuan inc Baichuan M2 32B achieves approximately 19.4 tokens per second decode speed with a time-to-first-token of 9988ms using Q4_K_M quantization.
For coding workloads, baichuan inc Baichuan M2 32B on MacBook Pro M4 Pro 48GB receives a C grade with 19.4 tok/s and 38K context.
On MacBook Pro M4 Pro 48GB, baichuan inc Baichuan M2 32B can safely use up to 38K 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-m4-pro-48gb" 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 |
| C49 |
Q4_K_M | 4 | 19.5 GB | Medium | C49 |
Q5_K_M | 5 | 23.0 GB | High | C48 |
Q6_KBest for your GPU | 6 | 26.2 GB | High | C48 |
Q8_0 | 8 | 34.2 GB | Very High | F0 |
F16 | 16 | 65.6 GB | Maximum | F0 |
Not always. MacBook Pro M4 Pro 48GB 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.