Can I Run / Qwen3 VL 32B Instruct / on NVIDIA L40
Can I Run Qwen3 VL 32B Instruct on a NVIDIA L40?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
33.4B
GPU memory
48.0GB
Smallest quant
Q2_K
Best fit
Q8_0
11 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 36.5 GB | 38.0 GB | 34.8 GB | +11.5 GB |
| Q6_K | 28.5 GB | 30.0 GB | 26.9 GB | +19.5 GB |
| Q5_K_M | 24.7 GB | 26.2 GB | 23.2 GB | +23.3 GB |
| Q5_K_S | 24.1 GB | 25.6 GB | 22.6 GB | +23.9 GB |
| Q4_1 | 21.9 GB | 23.4 GB | 20.6 GB | +26.1 GB |
| Q4_K_M | 21.3 GB | 22.8 GB | 19.8 GB | +26.8 GB |
| Q4_K_S | 20.1 GB | 21.6 GB | 18.8 GB | +27.9 GB |
| Q4_0 | 19.8 GB | 21.3 GB | 18.7 GB | +28.2 GB |
| Q3_K_M | 15.0 GB | 16.5 GB | 16.0 GB | +33.0 GB |
| Q3_K_S | 13.9 GB | 15.4 GB | 14.4 GB | +34.1 GB |
| Q2_K | 12.0 GB | 13.5 GB | 12.3 GB | +36.0 GB |
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Full model details
Qwen3 VL 32B Instruct →
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 VL 32B Instruct?
Yes. The NVIDIA L40's 48.0GB of VRAM is enough to run Qwen3 VL 32B Instruct at Q8_0 quantization (36.5GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 48.0GB. It uses about 36.5GB of memory and 38.0GB 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.