Can I Run / Qwen3.5-27B / on NVIDIA L40S
Can I Run Qwen3.5-27B on a NVIDIA L40S?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
27.0B
GPU memory
48.0GB
Smallest quant
Q4_K_M
Best fit
Q8_0
4 quantizations fit your 48.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 29.7 GB | 31.2 GB | 28.7 GB | +18.3 GB |
| Q6_K | 23.2 GB | 24.7 GB | 22.2 GB | +24.8 GB |
| Q5_K_M | 20.2 GB | 21.7 GB | 19.2 GB | +27.8 GB |
| Q4_K_M | 17.4 GB | 18.9 GB | 16.4 GB | +30.6 GB |
Try it in the cloud first
Don't want to download Qwen3.5-27B just to try it? Use a hosted API or rent a GPU by the second.
Affiliate links — we earn a commission at no cost to you.
Advertisement
Full model details
Qwen3.5-27B →
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 Qwen3.5-27B?
Yes. The NVIDIA L40S's 48.0GB of VRAM is enough to run Qwen3.5-27B at Q8_0 quantization (29.7GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 48.0GB. It uses about 29.7GB of memory and 31.2GB 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.