Can I Run Ministral 3 14B on a NVIDIA RTX 3080 10GB?
Runs at Q4_K_M — good quality with reasonable headroom.
1 quant fit your 10.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q4_K_MBEST | 9.5 GB | 11.0 GB | 8.5 GB | +0.5 GB |
Try it in the cloud first
Don't want to download Ministral 3 14B 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.
All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 10.0GB.
FAQ
Can the NVIDIA RTX 3080 10GB run Ministral 3 14B?
Yes. The NVIDIA RTX 3080 10GB's 10.0GB of VRAM is enough to run Ministral 3 14B at Q4_K_M quantization (9.5GB required).
What's the best quantization to use?
Q4_K_M is the highest-precision quantization that fits in your 10.0GB. It uses about 9.5GB of memory and 11.0GB 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.