Mac Studio M3 Ultra 256GBBudget pick
256 GB Unified (+76)
B
This setup is broadly balanced for this model.111 tok/s decode
~$6,999 MSRP
GLM-4 9B needs ~25.3 GB VRAM. NVIDIA B200 180GB has 180.0 GB. With Q4_K_M quantization, expect ~126 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
126.0 tok/s
TTFT
1537 ms
Safe context
128K
Memory
25.3 GB / 180.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 126.0 tok/s | 838 ms | 128K |
| Coding | B | Runs well | 126.0 tok/s | 1537 ms | 128K |
| Agentic Coding | B | Runs well | 126.0 tok/s | 2235 ms | 128K |
| Reasoning | B | Runs well | 126.0 tok/s | 1816 ms | 128K |
| RAG | B | Runs well | 126.0 tok/s | 2794 ms | 128K |
How GLM-4 9B (9B params) fits at each quantization level on NVIDIA B200 180GB (180.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B59 |
Q3_K_S | 3 | 4.4 GB | Low | B59 |
NVFP4 | 4 | 5.0 GB | Medium | B59 |
Q4_K_M | 4 | 5.5 GB | Medium | B59 |
Q5_K_M | 5 | 6.5 GB | High | B59 |
Q6_K | 6 | 7.4 GB | High | B59 |
Q8_0 | 8 | 9.6 GB | Very High | B59 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B59 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Upgrade options
Yes, NVIDIA B200 180GB can run GLM-4 9B with a B grade (Runs well). Expected decode speed: 126.0 tok/s.
GLM-4 9B (9B parameters) requires approximately 25.3 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 NVIDIA B200 180GB, GLM-4 9B achieves approximately 126.0 tokens per second decode speed with a time-to-first-token of 1537ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on NVIDIA B200 180GB receives a B grade with 126.0 tok/s and 128K context.
On NVIDIA B200 180GB, 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/glm-4-9b-on-b200-180gb" 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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