Can I Run / Qwen 3.5 4B / on NVIDIA RTX 3090 Ti
Can I Run Qwen 3.5 4B on a NVIDIA RTX 3090 Ti?
Yes
Runs at full precision (f32). Zero quality loss.
Model size
4.7B
GPU memory
24.0GB
Smallest quant
Q3_K_S
Best fit
f32
12 quantizations fit your 24.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| f32BEST | 19.8 GB | 21.3 GB | 1.3 GB | +4.2 GB |
| fp16 | 10.4 GB | 11.9 GB | 0.7 GB | +13.6 GB |
| Q8_0 | 6.0 GB | 7.5 GB | 4.5 GB | +18.0 GB |
| Q6_K | 4.9 GB | 6.4 GB | 3.5 GB | +19.1 GB |
| Q5_K_M | 4.3 GB | 5.8 GB | 3.1 GB | +19.7 GB |
| Q5_K_S | 4.2 GB | 5.7 GB | 3.0 GB | +19.8 GB |
| Q4_1 | 3.9 GB | 5.4 GB | 2.8 GB | +20.1 GB |
| Q4_K_M | 3.9 GB | 5.3 GB | 2.7 GB | +20.1 GB |
| Q4_K_S | 3.7 GB | 5.2 GB | 2.6 GB | +20.3 GB |
| Q4_0 | 3.6 GB | 5.1 GB | 2.6 GB | +20.4 GB |
| Q3_K_M | 3.0 GB | 4.5 GB | 2.3 GB | +21.0 GB |
| Q3_K_S | 2.8 GB | 4.3 GB | 2.1 GB | +21.2 GB |
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Full model details
Qwen 3.5 4B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA RTX 3090 Ti →
Top-ranked open-source models that fit in 24.0GB.
FAQ
Can the NVIDIA RTX 3090 Ti run Qwen 3.5 4B?
Yes. The NVIDIA RTX 3090 Ti's 24.0GB of VRAM is enough to run Qwen 3.5 4B at f32 quantization (19.8GB required).
What's the best quantization to use?
f32 is the highest-precision quantization that fits in your 24.0GB. It uses about 19.8GB of memory and 21.3GB 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.