MacBook Pro M4 Max 48GBBudget pick
48 GB Unified (+16)
C
This setup is broadly balanced for this model.68.3 tok/s decode
~$2,499 MSRP
glm 4 9b chat 1m needs ~10.6 GB VRAM. Radeon AI PRO R9700 32GB has 32.0 GB. With Q4_K_M quantization, expect ~69 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
68.8 tok/s
TTFT
2815 ms
Safe context
340K
Memory
10.6 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 | C | Runs well | 68.8 tok/s | 1535 ms | 340K |
| Coding | C | Runs well | 68.8 tok/s | 2815 ms | 340K |
| Agentic Coding | C | Runs well | 68.8 tok/s | 4094 ms | 340K |
| Reasoning | C | Runs well | 68.8 tok/s | 3327 ms | 340K |
| RAG | C | Runs well | 68.8 tok/s | 5118 ms | 340K |
How glm 4 9b chat 1m (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 | C43 |
Q3_K_S | 3 | 4.4 GB | Low | C44 |
NVFP4 | 4 | 5.0 GB | Medium | C44 |
Q4_K_M | 4 | 5.5 GB | Medium | C44 |
Q5_K_M | 5 | 6.5 GB | High | C44 |
Q6_K | 6 | 7.4 GB | High | C45 |
Q8_0 | 8 | 9.6 GB | Very High | C46 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | C49 |
Copy-paste commands to run glm 4 9b chat 1m on your machine.
Run
lms load hf-bartowski--glm-4-9b-chat-1m-gguf && lms server startUpgrade 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 chat 1m with a C grade (Runs well). Expected decode speed: 68.8 tok/s.
glm 4 9b chat 1m (9B parameters) requires approximately 10.6 GB of memory with Q4_K_M quantization.
The recommended quantization for glm 4 9b chat 1m is Q4_K_M, which balances quality and memory efficiency.
On Radeon AI PRO R9700 32GB, glm 4 9b chat 1m achieves approximately 68.8 tokens per second decode speed with a time-to-first-token of 2815ms using Q4_K_M quantization.
For coding workloads, glm 4 9b chat 1m on Radeon AI PRO R9700 32GB receives a C grade with 68.8 tok/s and 340K context.
On Radeon AI PRO R9700 32GB, glm 4 9b chat 1m can safely use up to 340K tokens of context. The model's official context limit is —, 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/hf-bartowski--glm-4-9b-chat-1m-gguf-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>
Preview: