Can I Run Qwen3 32B on a NVIDIA L40?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
32.8B
GPU memory
48.0GB
Smallest quant
Q2_K
Best fit
Q8_0
13 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 35.9 GB | 37.4 GB | 34.8 GB | +12.1 GB |
| Q6_K | 28.0 GB | 29.5 GB | 26.9 GB | +20.0 GB |
| Q5_K_M | 24.3 GB | 25.8 GB | 23.2 GB | +23.7 GB |
| Q5_K_S | 23.6 GB | 25.1 GB | 22.6 GB | +24.4 GB |
| Q5_0 | 23.6 GB | 25.1 GB | 22.6 GB | +24.4 GB |
| Q4_1 | 21.5 GB | 23.0 GB | 20.6 GB | +26.5 GB |
| Q4_K_M | 20.9 GB | 22.4 GB | 19.8 GB | +27.1 GB |
| Q4_K_S | 19.8 GB | 21.3 GB | 18.8 GB | +28.2 GB |
| Q4_0 | 19.4 GB | 20.9 GB | 18.7 GB | +28.6 GB |
| Q3_K_L | 15.6 GB | 17.1 GB | 17.3 GB | +32.4 GB |
| Q3_K_M | 14.7 GB | 16.2 GB | 16.0 GB | +33.3 GB |
| Q3_K_S | 13.6 GB | 15.1 GB | 14.4 GB | +34.4 GB |
| Q2_K | 11.8 GB | 13.3 GB | 12.3 GB | +36.2 GB |
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Full model details
Qwen3 32B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA L40 →
Top-ranked open-source models that fit in 48.0GB.
FAQ
Can the NVIDIA L40 run Qwen3 32B?
Yes. The NVIDIA L40's 48.0GB of VRAM is enough to run Qwen3 32B at Q8_0 quantization (35.9GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 48.0GB. It uses about 35.9GB of memory and 37.4GB 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.