glm 4 9b chat 1m needs ~10.9 GB VRAM. RTX 5090 32GB has 32.0 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
335K
Memory
10.9 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 | 126.0 tok/s | 838 ms | 335K |
| Coding | C | Runs well | 126.0 tok/s | 1537 ms | 335K |
| Agentic Coding | C | Runs well | 126.0 tok/s | 2235 ms | 335K |
| Reasoning | C | Runs well | 126.0 tok/s | 1816 ms | 335K |
| RAG | C | Runs well | 126.0 tok/s | 2794 ms | 335K |
How glm 4 9b chat 1m (9B params) fits at each quantization level on RTX 5090 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 startYes, RTX 5090 32GB can run glm 4 9b chat 1m with a C grade (Runs well). Expected decode speed: 126.0 tok/s.
glm 4 9b chat 1m (9B parameters) requires approximately 10.9 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 5090 32GB, glm 4 9b chat 1m 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 chat 1m on RTX 5090 32GB receives a C grade with 126.0 tok/s and 335K context.
On RTX 5090 32GB, glm 4 9b chat 1m can safely use up to 335K 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-5090-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: