Can I Run Qwen3 4B on a NVIDIA RTX 4070 Ti?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
4.0B
GPU memory
12.0GB
Smallest quant
Q2_K
Best fit
Q8_0
13 quantizations fit your 12.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 5.3 GB | 6.8 GB | 4.3 GB | +6.8 GB |
| Q6_K | 4.3 GB | 5.8 GB | 3.3 GB | +7.7 GB |
| Q5_K_M | 3.8 GB | 5.3 GB | 2.9 GB | +8.2 GB |
| Q5_K_S | 3.8 GB | 5.3 GB | 2.8 GB | +8.2 GB |
| Q5_0 | 3.8 GB | 5.3 GB | 2.8 GB | +8.3 GB |
| Q4_1 | 3.5 GB | 5.0 GB | 2.6 GB | +8.5 GB |
| Q4_K_M | 3.4 GB | 4.9 GB | 2.5 GB | +8.6 GB |
| Q4_K_S | 3.3 GB | 4.8 GB | 2.4 GB | +8.7 GB |
| Q4_0 | 3.3 GB | 4.8 GB | 2.4 GB | +8.8 GB |
| Q3_K_L | 2.8 GB | 4.3 GB | 2.2 GB | +9.2 GB |
| Q3_K_M | 2.7 GB | 4.2 GB | 2.1 GB | +9.3 GB |
| Q3_K_S | 2.5 GB | 4.0 GB | 1.9 GB | +9.5 GB |
| Q2_K | 2.3 GB | 3.8 GB | 1.7 GB | +9.7 GB |
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Full model details
Qwen3 4B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA RTX 4070 Ti →
Top-ranked open-source models that fit in 12.0GB.
FAQ
Can the NVIDIA RTX 4070 Ti run Qwen3 4B?
Yes. The NVIDIA RTX 4070 Ti's 12.0GB of VRAM is enough to run Qwen3 4B at Q8_0 quantization (5.3GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 12.0GB. It uses about 5.3GB of memory and 6.8GB 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.