glm 4 9b chat 1m needs ~8.9 GB VRAM. RTX 3500 Ada Laptop 12GB has 12.0 GB. With Q4_K_M quantization, expect ~45 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
44.7 tok/s
TTFT
4333 ms
Safe context
62K
Memory
8.9 GB / 12.0 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 | 44.7 tok/s | 2364 ms | 62K |
| Coding | C | Runs well | 44.7 tok/s | 4333 ms | 62K |
| Agentic Coding | C | Tight fit | 44.7 tok/s | 6303 ms | 62K |
| Reasoning | C | Runs well | 44.7 tok/s | 5121 ms | 62K |
| RAG | C | Tight fit | 44.7 tok/s | 7879 ms | 62K |
How glm 4 9b chat 1m (9B params) fits at each quantization level on RTX 3500 Ada Laptop 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C50 |
Q3_K_S | 3 | 4.4 GB | Low | C51 |
NVFP4 | 4 | 5.0 GB | Medium | C52 |
Q4_K_M | 4 | 5.5 GB | Medium | C53 |
Q5_K_M | 5 | 6.5 GB | High | C52 |
Q6_KBest for your GPU | 6 | 7.4 GB | High | C52 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |
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 startYes, RTX 3500 Ada Laptop 12GB can run glm 4 9b chat 1m with a C grade (Runs well). Expected decode speed: 44.7 tok/s.
glm 4 9b chat 1m (9B parameters) requires approximately 8.9 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 RTX 3500 Ada Laptop 12GB, glm 4 9b chat 1m achieves approximately 44.7 tokens per second decode speed with a time-to-first-token of 4333ms using Q4_K_M quantization.
For coding workloads, glm 4 9b chat 1m on RTX 3500 Ada Laptop 12GB receives a C grade with 44.7 tok/s and 62K context.
On RTX 3500 Ada Laptop 12GB, glm 4 9b chat 1m can safely use up to 62K 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-rtx-3500-ada-laptop-12gb" 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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