Can I Run / Qwen 3.5 9B / on NVIDIA L40S
Can I Run Qwen 3.5 9B on a NVIDIA L40S?
Yes
Runs at full precision (fp16). Zero quality loss.
Model size
9.0B
GPU memory
48.0GB
Smallest quant
Q4_K_M
Best fit
fp16
5 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 19.0 GB | 20.5 GB | 18.0 GB | +29.0 GB |
| Q8_0 | 10.6 GB | 12.1 GB | 9.6 GB | +37.4 GB |
| Q6_K | 8.4 GB | 9.9 GB | 7.4 GB | +39.6 GB |
| Q5_K_M | 7.4 GB | 8.9 GB | 6.4 GB | +40.6 GB |
| Q4_K_M | 6.5 GB | 8.0 GB | 5.5 GB | +41.5 GB |
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Full model details
Qwen 3.5 9B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA L40S →
Top-ranked open-source models that fit in 48.0GB.
FAQ
Can the NVIDIA L40S run Qwen 3.5 9B?
Yes. The NVIDIA L40S's 48.0GB of VRAM is enough to run Qwen 3.5 9B at fp16 quantization (19.0GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 48.0GB. It uses about 19.0GB of memory and 20.5GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.