GLM-4 9B needs ~7.8 GB VRAM. RTX 4060 8GB has 8.0 GB. With Q4_K_M quantization, expect ~36 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 with offload
Decode
36.4 tok/s
TTFT
5320 ms
Safe context
21K
Memory
7.8 GB / 8.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 36.4 tok/s | 2902 ms | 21K |
| Coding | A | Runs with offload | 36.4 tok/s | 5320 ms | 21K |
| Agentic Coding | A | Runs with offload (needs ~0.3 GB host RAM) | 24.6 tok/s | 11463 ms | 21K |
| Reasoning | A | Runs with offload | 36.4 tok/s | 6287 ms | 21K |
| RAG | A | Runs with offload (needs ~0.3 GB host RAM) | 24.6 tok/s | 14329 ms | 21K |
How GLM-4 9B (9B params) fits at each quantization level on RTX 4060 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | A75 |
Q3_K_S | 3 | 4.4 GB | Low | A75 |
NVFP4Best for your GPU | 4 | 5.0 GB | Medium | A74 |
Q4_K_M | 4 | 5.5 GB | Medium | F0 |
Q5_K_M | 5 | 6.5 GB | High | F0 |
Q6_K | 6 | 7.4 GB | High | F0 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |
Copy-paste commands to run GLM-4 9B on your machine.
Run
ollama run glm4Yes, RTX 4060 8GB can run GLM-4 9B with a A grade (Runs with offload). Expected decode speed: 36.4 tok/s.
GLM-4 9B (9B parameters) requires approximately 7.8 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 4060 8GB, GLM-4 9B achieves approximately 36.4 tokens per second decode speed with a time-to-first-token of 5320ms using Q4_K_M quantization.
For coding workloads, GLM-4 9B on RTX 4060 8GB receives a A grade with 36.4 tok/s and 21K context.
On RTX 4060 8GB, GLM-4 9B can safely use up to 21K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/glm-4-9b-on-rtx-4060-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: