GLM-4 9B needs ~13.9 GB VRAM. MacBook Pro M3 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~48 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
47.8 tok/s
TTFT
4049 ms
Safe context
128K
Memory
13.9 GB / 46.1 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 | B | Runs well | 47.8 tok/s | 2209 ms | 128K |
| Coding | B | Runs well | 47.8 tok/s | 4049 ms | 128K |
| Agentic Coding | B | Runs well | 47.8 tok/s | 5889 ms | 128K |
| Reasoning | B | Runs well | 47.8 tok/s | 4785 ms | 128K |
| RAG | B | Runs well | 47.8 tok/s | 7362 ms | 128K |
How GLM-4 9B (9B params) fits at each quantization level on MacBook Pro M3 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B63 |
Q3_K_S | 3 | 4.4 GB | Low | B63 |
NVFP4 | 4 | 5.0 GB | Medium | B63 |
Q4_K_M | 4 | 5.5 GB | Medium | B63 |
Q5_K_M | 5 | 6.5 GB | High | B64 |
Q6_K | 6 | 7.4 GB | High | B64 |
Q8_0 | 8 | 9.6 GB | Very High | B64 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B67 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Upgrade options
Raises estimated decode speed by about 56%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Raises estimated decode speed by about 132%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 93%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, MacBook Pro M3 Max 64GB can run GLM-4 9B with a B grade (Runs well). Expected decode speed: 47.8 tok/s.
GLM-4 9B (9B parameters) requires approximately 13.9 GB of memory with Q4_K_M quantization.
The recommended quantization for GLM-4 9B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M3 Max 64GB, GLM-4 9B achieves approximately 47.8 tokens per second decode speed with a time-to-first-token of 4049ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on MacBook Pro M3 Max 64GB receives a B grade with 47.8 tok/s and 128K context.
On MacBook Pro M3 Max 64GB, GLM-4 9B can safely use up to 128K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
Not always. MacBook Pro M3 Max 64GB 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/glm-4-9b-on-m3-max-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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