Can I Run / Qwen 3.6 35B A3B / on NVIDIA L40S
Can I Run Qwen 3.6 35B A3B on a NVIDIA L40S?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
36.0B
GPU memory
48.0GB
Smallest quant
Q3_K_S
Best fit
Q8_0
9 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 39.3 GB | 40.8 GB | 36.9 GB | +8.8 GB |
| Q6_K | 30.7 GB | 32.2 GB | 29.3 GB | +17.3 GB |
| Q5_K_M | 26.6 GB | 28.1 GB | 26.5 GB | +21.4 GB |
| Q5_K_S | 25.8 GB | 27.3 GB | 24.9 GB | +22.2 GB |
| Q4_K_M | 22.8 GB | 24.3 GB | 22.1 GB | +25.2 GB |
| Q4_K_S | 21.6 GB | 23.1 GB | 20.9 GB | +26.4 GB |
| Q4_0 | 21.3 GB | 22.8 GB | 1.1 GB | +26.8 GB |
| Q3_K_M | 16.1 GB | 17.6 GB | 16.6 GB | +31.9 GB |
| Q3_K_S | 14.9 GB | 16.4 GB | 15.4 GB | +33.1 GB |
Try it in the cloud first
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Full model details
Qwen 3.6 35B A3B →
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 3.6 35B A3B?
Yes. The NVIDIA L40S's 48.0GB of VRAM is enough to run Qwen 3.6 35B A3B at Q8_0 quantization (39.3GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 48.0GB. It uses about 39.3GB of memory and 40.8GB 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.