RTX 5070 12GBBudget pick12 GB VRAM (+1)672 GB/s (+56)
B
This setup is broadly balanced for this model.77.1 tok/s decode
~$549 MSRP
glm 4 9b chat 1m needs ~8.8 GB VRAM. RTX 2080 Ti 11GB has 11.0 GB. With Q4_K_M quantization, expect ~73 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
72.9 tok/s
TTFT
2655 ms
Safe context
49K
Memory
8.8 GB / 11.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 72.9 tok/s | 1448 ms | 49K |
| Coding | B | Runs well | 72.9 tok/s | 2655 ms | 49K |
| Agentic Coding | C | Tight fit | 72.9 tok/s | 3861 ms | 49K |
| Reasoning | B | Runs well | 72.9 tok/s | 3137 ms | 49K |
| RAG | C | Tight fit | 72.9 tok/s | 4826 ms | 49K |
How glm 4 9b chat 1m (9B params) fits at each quantization level on RTX 2080 Ti 11GB (11.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C51 |
Q3_K_S | 3 | 4.4 GB | Low | C52 |
NVFP4 | 4 | 5.0 GB | Medium | C53 |
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 startUpgrade options
RTX 5070 12GBBudget pick~$549 MSRP
RTX 3080 12GBBest valueRaises estimated decode speed by about 73%.
~$799 MSRP
RTX 3080 Ti 12GBNVIDIA upgradeRaises estimated decode speed by about 69%.
~$1,199 MSRP
Yes, RTX 2080 Ti 11GB can run glm 4 9b chat 1m with a B grade (Runs well). Expected decode speed: 72.9 tok/s.
glm 4 9b chat 1m (9B parameters) requires approximately 8.8 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 2080 Ti 11GB, glm 4 9b chat 1m achieves approximately 72.9 tokens per second decode speed with a time-to-first-token of 2655ms using Q4_K_M quantization.
For coding workloads, glm 4 9b chat 1m on RTX 2080 Ti 11GB receives a B grade with 72.9 tok/s and 49K context.
On RTX 2080 Ti 11GB, glm 4 9b chat 1m can safely use up to 49K 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-2080-ti-11gb" 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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