MacBook Pro M4 Max 48GBBudget pick
48 GB Unified (+16)
A
This setup is broadly balanced for this model.74.7 tok/s decode
~$2,499 MSRP
GLM-4 9B needs ~10.2 GB VRAM. Radeon AI PRO R9700 32GB has 32.0 GB. With Q4_K_M quantization, expect ~75 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
75.2 tok/s
TTFT
2574 ms
Safe context
128K
Memory
10.2 GB / 32.0 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 | 75.2 tok/s | 1404 ms | 128K |
| Coding | B | Runs well | 75.2 tok/s | 2574 ms | 128K |
| Agentic Coding | B | Runs well | 75.2 tok/s | 3743 ms | 128K |
| Reasoning | B | Runs well | 75.2 tok/s | 3041 ms | 128K |
| RAG | B | Runs well | 75.2 tok/s | 4679 ms | 128K |
How GLM-4 9B (9B params) fits at each quantization level on Radeon AI PRO R9700 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B65 |
Q3_K_S | 3 | 4.4 GB | Low | B65 |
NVFP4 | 4 | 5.0 GB | Medium | B65 |
Q4_K_M | 4 | 5.5 GB | Medium | B65 |
Q5_K_M | 5 | 6.5 GB | High | B66 |
Q6_K | 6 | 7.4 GB | High | B66 |
Q8_0 | 8 | 9.6 GB | Very High | B67 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | A71 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Upgrade options
~$2,499 MSRP
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, Radeon AI PRO R9700 32GB can run GLM-4 9B with a B grade (Runs well). Expected decode speed: 75.2 tok/s.
GLM-4 9B (9B parameters) requires approximately 10.2 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 Radeon AI PRO R9700 32GB, GLM-4 9B achieves approximately 75.2 tokens per second decode speed with a time-to-first-token of 2574ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on Radeon AI PRO R9700 32GB receives a B grade with 75.2 tok/s and 128K context.
On Radeon AI PRO R9700 32GB, 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-radeon-ai-pro-r9700-32gb" 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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