GLM-4 9B needs ~9.7 GB VRAM. NVIDIA L4 24GB has 24.0 GB. With Q4_K_M quantization, expect ~39 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
38.8 tok/s
TTFT
4983 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 | B | Runs well | 38.8 tok/s | 2718 ms | 128K |
| Coding | B | Runs well | 38.8 tok/s | 4983 ms | 128K |
| Agentic Coding | B | Runs well | 38.8 tok/s | 7249 ms | 128K |
| Reasoning | B | Runs well | 38.8 tok/s | 5889 ms | 128K |
| RAG | B | Runs well | 38.8 tok/s | 9061 ms | 128K |
How GLM-4 9B (9B params) fits at each quantization level on NVIDIA L4 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 glm4Upgrade options
RTX 5090 32GBBudget pickRaises estimated decode speed by about 225%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
RTX PRO 4500 Blackwell 32GBBest valueRaises estimated decode speed by about 225%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
RTX 5000 Ada 32GBNVIDIA upgradeRaises estimated decode speed by about 137%.
Adds memory headroom for longer context windows and future model growth.
~$4,000 MSRP
Yes, NVIDIA L4 24GB can run GLM-4 9B with a B grade (Runs well). Expected decode speed: 38.8 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 NVIDIA L4 24GB, GLM-4 9B achieves approximately 38.8 tokens per second decode speed with a time-to-first-token of 4983ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on NVIDIA L4 24GB receives a B grade with 38.8 tok/s and 128K context.
On NVIDIA L4 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-l4-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: