glm 4 9b chat 1m needs ~9.3 GB VRAM. RTX 4080 Super 16GB has 16.0 GB. With Q4_K_M quantization, expect ~111 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
111.3 tok/s
TTFT
1740 ms
Safe context
117K
Memory
9.3 GB / 16.0 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 | 111.3 tok/s | 949 ms | 117K |
| Coding | C | Runs well | 111.3 tok/s | 1740 ms | 117K |
| Agentic Coding | B | Runs well | 111.3 tok/s | 2531 ms | 117K |
| Reasoning | C | Runs well | 111.3 tok/s | 2056 ms | 117K |
| RAG | B | Runs well | 111.3 tok/s | 3163 ms | 117K |
How glm 4 9b chat 1m (9B params) fits at each quantization level on RTX 4080 Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C47 |
Q3_K_S | 3 | 4.4 GB | Low | C48 |
NVFP4 | 4 |
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 4080 Super 16GB can run glm 4 9b chat 1m with a C grade (Runs well). Expected decode speed: 111.3 tok/s.
glm 4 9b chat 1m (9B parameters) requires approximately 9.3 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 4080 Super 16GB, glm 4 9b chat 1m achieves approximately 111.3 tokens per second decode speed with a time-to-first-token of 1740ms using Q4_K_M quantization.
For coding workloads, glm 4 9b chat 1m on RTX 4080 Super 16GB receives a C grade with 111.3 tok/s and 117K context.
On RTX 4080 Super 16GB, glm 4 9b chat 1m can safely use up to 117K 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-4080-super-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
5.0 GB |
| Medium |
| C49 |
Q4_K_M | 4 | 5.5 GB | Medium | C49 |
Q5_K_M | 5 | 6.5 GB | High | C50 |
Q6_K | 6 | 7.4 GB | High | C51 |
Q8_0Best for your GPU | 8 | 9.6 GB | Very High | C51 |
F16 | 16 | 18.5 GB | Maximum | F0 |