GLM-4 9B needs ~8.9 GB VRAM. RTX 2000 Ada 16GB has 16.0 GB. With Q4_K_M quantization, expect ~44 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
43.6 tok/s
TTFT
4440 ms
Safe context
128K
Memory
8.9 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 | A | Runs well | 43.6 tok/s | 2422 ms | 128K |
| Coding | A | Runs well | 43.6 tok/s | 4440 ms | 128K |
| Agentic Coding | A | Runs well | 43.6 tok/s | 6458 ms | 128K |
| Reasoning | A | Runs well | 43.6 tok/s | 5247 ms | 128K |
| RAG | A | Runs well | 43.6 tok/s | 8072 ms | 128K |
How GLM-4 9B (9B params) fits at each quantization level on RTX 2000 Ada 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B69 |
Q3_K_S | 3 | 4.4 GB | Low | B70 |
NVFP4 | 4 | 5.0 GB | Medium | A70 |
Q4_K_M | 4 | 5.5 GB | Medium | A71 |
Q5_K_M | 5 | 6.5 GB | High | A72 |
Q6_K | 6 | 7.4 GB | High | A73 |
Q8_0Best for your GPU | 8 | 9.6 GB | Very High | A73 |
F16 | 16 | 18.5 GB | Maximum | F0 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3 14B | 14B | S | 27.7 tok/s | |
 Phi-4-reasoning-plus 14B | 14.7B | S | 26.2 tok/s | |
 GPT-OSS 20B | 21B | A | 24.4 tok/s | |
 Ministral 3 14B | 14B | S | 27.6 tok/s | |
| Codestral 2 25.08 | 22B | A | 9.5 tok/s |
Yes, RTX 2000 Ada 16GB can run GLM-4 9B with a A grade (Runs well). Expected decode speed: 43.6 tok/s.
GLM-4 9B (9B parameters) requires approximately 8.9 GB of memory with Q4_K_M quantization.
The recommended quantization for GLM-4 9B is Q4_K_M, which balances quality and memory efficiency.
On RTX 2000 Ada 16GB, GLM-4 9B achieves approximately 43.6 tokens per second decode speed with a time-to-first-token of 4440ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on RTX 2000 Ada 16GB receives a A grade with 43.6 tok/s and 128K context.
On RTX 2000 Ada 16GB, GLM-4 9B can safely use up to 128K tokens of context. The model's official context limit is 128K, 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/glm-4-9b-on-rtx-2000-ada-16gb" 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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