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 M2 32B Q4 K M needs ~29.4 GB VRAM. MacBook Pro M4 Max 48GB has 34.6 GB. With Q4_K_M quantization, expect ~18 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
30.8 tok/s
TTFT
6292 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 | 30.8 tok/s | 3432 ms | 38K |
| Coding | C | Tight fit | 17.6 tok/s | 10986 ms | 38K |
| Agentic Coding | C | Runs with offload | 30.8 tok/s | 9152 ms | 38K |
| Reasoning | C | Tight fit | 30.8 tok/s | 7436 ms | 38K |
| RAG | C | Runs with offload | 30.8 tok/s | 11441 ms | 38K |
How Baichuan M2 32B Q4 K M (32B params) fits at each quantization level on MacBook Pro M4 Max 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 M2 32B Q4 K M on your machine.
Run
lms load hf-baichuan-inc--baichuan-m2-32b-q4-k-m-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.
~$3,999 MSRP
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, MacBook Pro M4 Max 48GB can run Baichuan M2 32B Q4 K M with a C grade (Tight fit). Expected decode speed: 17.6 tok/s.
Baichuan M2 32B Q4 K M (32B parameters) requires approximately 29.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Baichuan M2 32B Q4 K M is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Max 48GB, Baichuan M2 32B Q4 K M achieves approximately 17.6 tokens per second decode speed with a time-to-first-token of 10986ms using Q4_K_M quantization.
For coding workloads, Baichuan M2 32B Q4 K M on MacBook Pro M4 Max 48GB receives a C grade with 17.6 tok/s and 38K context.
On MacBook Pro M4 Max 48GB, Baichuan M2 32B Q4 K M 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-baichuan-inc--baichuan-m2-32b-q4-k-m-gguf-on-m4-max-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 Max 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.