~$329 MSRP
glm 4 9b chat 1m needs ~8.7 GB VRAM. RTX 3080 10GB has 10.0 GB. With Q4_K_M quantization, expect ~105 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
Tight fit
Decode
105.2 tok/s
TTFT
1840 ms
Safe context
35K
Memory
8.7 GB / 10.0 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 | Tight fit | 105.2 tok/s | 1004 ms | 35K |
| Coding | C | Tight fit | 105.2 tok/s | 1840 ms | 35K |
| Agentic Coding | C | Runs with offload | 105.2 tok/s | 2677 ms | 35K |
| Reasoning | C | Tight fit | 105.2 tok/s | 2175 ms | 35K |
| RAG | C | Runs with offload | 105.2 tok/s | 3346 ms | 35K |
How glm 4 9b chat 1m (9B params) fits at each quantization level on RTX 3080 10GB (10.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C52 |
Q3_K_S | 3 | 4.4 GB | Low | C53 |
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 startUpgrade options
~$329 MSRP
~$549 MSRP
~$599 MSRP
Yes, RTX 3080 10GB can run glm 4 9b chat 1m with a C grade (Tight fit). Expected decode speed: 105.2 tok/s.
glm 4 9b chat 1m (9B parameters) requires approximately 8.7 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 3080 10GB, glm 4 9b chat 1m achieves approximately 105.2 tokens per second decode speed with a time-to-first-token of 1840ms using Q4_K_M quantization.
For coding workloads, glm 4 9b chat 1m on RTX 3080 10GB receives a C grade with 105.2 tok/s and 35K context.
On RTX 3080 10GB, glm 4 9b chat 1m can safely use up to 35K 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-3080-10gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| C53 |
Q4_K_M | 4 | 5.5 GB | Medium | C53 |
Q5_K_MBest for your GPU | 5 | 6.5 GB | High | C52 |
Q6_K | 6 | 7.4 GB | High | F0 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |