Can I Run / Qwen3.5-27B / on NVIDIA H200

Can I Run Qwen3.5-27B on a NVIDIA H200?

Yes

Runs at full precision (f32). Zero quality loss.

Model size
27.8B
GPU memory
141GB
Smallest quant
Q3_K_S
Best fit
f32

12 quantizations fit your 141GB

QuantMin VRAMRecommendedFile sizeHeadroom
f32BEST112.2 GB113.7 GB1.8 GB+28.8 GB
fp1656.6 GB58.1 GB0.9 GB+84.4 GB
Q8_030.5 GB32.0 GB28.6 GB+110.5 GB
Q6_K23.9 GB25.4 GB22.4 GB+117.1 GB
Q5_K_M20.7 GB22.2 GB19.6 GB+120.3 GB
Q5_K_S20.2 GB21.7 GB18.9 GB+120.8 GB
Q4_118.4 GB19.9 GB17.2 GB+122.6 GB
Q4_K_M17.9 GB19.4 GB16.7 GB+123.2 GB
Q4_K_S16.9 GB18.4 GB15.8 GB+124.1 GB
Q4_016.6 GB18.1 GB15.7 GB+124.4 GB
Q3_K_M12.6 GB14.1 GB13.5 GB+128.4 GB
Q3_K_S11.7 GB13.2 GB12.3 GB+129.3 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 H200

Top-ranked open-source models that fit in 141GB.

FAQ

Can the NVIDIA H200 run Qwen3.5-27B?

Yes. The NVIDIA H200's 141GB of VRAM is enough to run Qwen3.5-27B at f32 quantization (112.2GB required).

What's the best quantization to use?

f32 is the highest-precision quantization that fits in your 141GB. It uses about 112.2GB of memory and 113.7GB 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.