GLM-4 9B needs ~9.7 GB VRAM. RTX A5500 24GB has 24.0 GB. With Q4_K_M quantization, expect ~119 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
119.3 tok/s
TTFT
1622 ms
Safe context
128K
Memory
9.7 GB / 24.0 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 | 119.3 tok/s | 885 ms | 128K |
| Coding | A | Runs well | 119.3 tok/s | 1622 ms | 128K |
| Agentic Coding | A | Runs well | 119.3 tok/s | 2360 ms | 128K |
| Reasoning | A | Runs well | 119.3 tok/s | 1917 ms | 128K |
| RAG | A | Runs well | 119.3 tok/s | 2949 ms | 128K |
How GLM-4 9B (9B params) fits at each quantization level on RTX A5500 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B66 |
Q3_K_S | 3 | 4.4 GB | Low | B67 |
NVFP4 | 4 | 5.0 GB | Medium | B67 |
Q4_K_M | 4 | 5.5 GB | Medium | B67 |
Q5_K_M | 5 | 6.5 GB | High | B68 |
Q6_K | 6 | 7.4 GB | High | B68 |
Q8_0 | 8 | 9.6 GB | Very High | B70 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | A71 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 90.6 tok/s | |
| Qwen 3.5 27B | 27B | S | 39.3 tok/s | |
| Qwen 3.6 27B | 27B | S | 39.4 tok/s | |
| Qwen3-VL 30B A3B Instruct | 30B | S | 93.7 tok/s | |
| Qwen 3.5 35B A3B | 35B | A | 50.7 tok/s |
Yes, RTX A5500 24GB can run GLM-4 9B with a A grade (Runs well). Expected decode speed: 119.3 tok/s.
GLM-4 9B (9B parameters) requires approximately 9.7 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 A5500 24GB, GLM-4 9B achieves approximately 119.3 tokens per second decode speed with a time-to-first-token of 1622ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on RTX A5500 24GB receives a A grade with 119.3 tok/s and 128K context.
On RTX A5500 24GB, 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-a5500-24gb" 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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