GLM-4 9B needs ~17.4 GB VRAM. MacBook Pro M2 Max 96GB has 69.1 GB. With Q4_K_M quantization, expect ~46 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
46.2 tok/s
TTFT
4189 ms
Safe context
128K
Memory
17.4 GB / 69.1 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 | 46.2 tok/s | 2285 ms | 128K |
| Coding | B | Runs well | 46.2 tok/s | 4189 ms | 128K |
| Agentic Coding | B | Runs well | 46.2 tok/s | 6093 ms | 128K |
| Reasoning | B | Runs well | 46.2 tok/s | 4950 ms | 128K |
| RAG | B | Runs well | 46.2 tok/s | 7616 ms | 128K |
How GLM-4 9B (9B params) fits at each quantization level on MacBook Pro M2 Max 96GB (69.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B62 |
Q3_K_S | 3 | 4.4 GB | Low | B62 |
NVFP4 | 4 | 5.0 GB | Medium | B62 |
Q4_K_M | 4 | 5.5 GB | Medium | B62 |
Q5_K_M | 5 | 6.5 GB | High | B62 |
Q6_K | 6 | 7.4 GB | High | B62 |
Q8_0 | 8 | 9.6 GB | Very High | B62 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B64 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Opciones de mejora
Sube la velocidad estimada de decodificación alrededor de un 100%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$3,999 MSRP
Sube la velocidad estimada de decodificación alrededor de un 90%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$3,999 MSRP
Sube la velocidad estimada de decodificación alrededor de un 62%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$4,999 MSRP
Yes, MacBook Pro M2 Max 96GB can run GLM-4 9B with a B grade (Runs well). Expected decode speed: 46.2 tok/s.
GLM-4 9B (9B parameters) requires approximately 17.4 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 M2 Max 96GB, GLM-4 9B achieves approximately 46.2 tokens per second decode speed with a time-to-first-token of 4189ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on MacBook Pro M2 Max 96GB receives a B grade with 46.2 tok/s and 128K context.
On MacBook Pro M2 Max 96GB, 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 M2 Max 96GB 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-m2-max-96gb" 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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