Can I Run / granite 4.1 3b / on NVIDIA GTX 1650
Can I Run granite 4.1 3b on a NVIDIA GTX 1650?
Yes
Runs comfortably at Q6_K — minimal quality loss.
Model size
3.4B
GPU memory
4.0GB
Smallest quant
Q3_K_S
Best fit
Q6_K
9 quantizations fit your 4.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 3.8 GB | 5.3 GB | 2.8 GB | +0.2 GB |
| Q5_K_M | 3.4 GB | 4.9 GB | 2.4 GB | +0.6 GB |
| Q5_K_S | 3.4 GB | 4.8 GB | 2.4 GB | +0.6 GB |
| Q4_1 | 3.1 GB | 4.6 GB | 2.2 GB | +0.9 GB |
| Q4_K_M | 3.1 GB | 4.6 GB | 2.1 GB | +0.9 GB |
| Q4_K_S | 3.0 GB | 4.5 GB | 2.0 GB | +1.0 GB |
| Q4_0 | 2.9 GB | 4.4 GB | 2.0 GB | +1.1 GB |
| Q3_K_M | 2.4 GB | 3.9 GB | 1.7 GB | +1.6 GB |
| Q3_K_S | 2.3 GB | 3.8 GB | 1.6 GB | +1.7 GB |
Try it in the cloud first
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Full model details
granite 4.1 3b →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA GTX 1650 →
Top-ranked open-source models that fit in 4.0GB.
FAQ
Can the NVIDIA GTX 1650 run granite 4.1 3b?
Yes. The NVIDIA GTX 1650's 4.0GB of VRAM is enough to run granite 4.1 3b at Q6_K quantization (3.8GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 4.0GB. It uses about 3.8GB of memory and 5.3GB 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.