GLM-4 9B needs ~8.7 GB VRAM. MacBook Pro M4 16GB has 11.5 GB. With Q4_K_M quantization, expect ~16 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
15.8 tok/s
TTFT
12225 ms
Safe context
89K
Memory
8.7 GB / 11.5 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 | A | Runs well | 15.8 tok/s | 6668 ms | 89K |
| Coding | A | Runs well | 15.8 tok/s | 12225 ms | 89K |
| Agentic Coding | A | Runs well | 15.8 tok/s | 17782 ms | 89K |
| Reasoning | A | Runs well | 15.8 tok/s | 14448 ms | 89K |
| RAG | A | Runs well | 15.8 tok/s | 22228 ms | 89K |
How GLM-4 9B (9B params) fits at each quantization level on MacBook Pro M4 16GB (11.5 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | A72 |
Q3_K_S | 3 | 4.4 GB | Low | A73 |
NVFP4 | 4 | 5.0 GB | Medium | A74 |
Q4_K_M | 4 | 5.5 GB | Medium | A74 |
Q5_K_M | 5 | 6.5 GB | High | A74 |
Q6_KBest for your GPU | 6 | 7.4 GB | High | A73 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3 14B | 14B | A | 7.5 tok/s | |
 Ministral 3 14B | 14B | B | 7.4 tok/s | |
 OLMo 2 13B | 13B | B | 8.5 tok/s | |
| Pixtral 12B | 12B | B | 9.8 tok/s |
Yes, MacBook Pro M4 16GB can run GLM-4 9B with a A grade (Runs well). Expected decode speed: 15.8 tok/s.
GLM-4 9B (9B parameters) requires approximately 8.7 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 M4 16GB, GLM-4 9B achieves approximately 15.8 tokens per second decode speed with a time-to-first-token of 12225ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on MacBook Pro M4 16GB receives a A grade with 15.8 tok/s and 89K context.
On MacBook Pro M4 16GB, GLM-4 9B can safely use up to 89K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
Not always. MacBook Pro M4 16GB 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-m4-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: