Can I Run / Qwen 3.6 35B A3B / on NVIDIA A100 40GB
Can I Run Qwen 3.6 35B A3B on a NVIDIA A100 40GB?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
35.0B
GPU memory
40.0GB
Smallest quant
Q4_K_M
Best fit
Q8_0
4 quantizations fit your 40.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 38.2 GB | 39.7 GB | 37.2 GB | +1.8 GB |
| Q6_K | 29.8 GB | 31.3 GB | 28.8 GB | +10.2 GB |
| Q5_K_M | 25.9 GB | 27.4 GB | 24.9 GB | +14.1 GB |
| Q4_K_M | 22.2 GB | 23.7 GB | 21.2 GB | +17.8 GB |
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Full model details
Qwen 3.6 35B A3B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA A100 40GB →
Top-ranked open-source models that fit in 40.0GB.
FAQ
Can the NVIDIA A100 40GB run Qwen 3.6 35B A3B?
Yes. The NVIDIA A100 40GB's 40.0GB of VRAM is enough to run Qwen 3.6 35B A3B at Q8_0 quantization (38.2GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 40.0GB. It uses about 38.2GB of memory and 39.7GB 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.