Can I Run DeepSeek R1 Distill Qwen 32B on a NVIDIA L40?
Runs at Q8_0 — near-lossless quality.
4 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 35.9 GB | 37.4 GB | 34.9 GB | +12.1 GB |
| Q6_K | 28.0 GB | 29.5 GB | 27.0 GB | +20.0 GB |
| Q5_K_M | 24.3 GB | 25.8 GB | 23.3 GB | +23.7 GB |
| Q4_K_M | 20.9 GB | 22.4 GB | 19.9 GB | +27.1 GB |
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Top-ranked open-source models that fit in 48.0GB.
FAQ
Can the NVIDIA L40 run DeepSeek R1 Distill Qwen 32B?
Yes. The NVIDIA L40's 48.0GB of VRAM is enough to run DeepSeek R1 Distill Qwen 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.