Can I Run / Ministral 3 8B 2512 / on NVIDIA RTX 5080
Can I Run Ministral 3 8B 2512 on a NVIDIA RTX 5080?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
8.9B
GPU memory
16.0GB
Smallest quant
Q2_K
Best fit
Q8_0
11 quantizations fit your 16.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 10.5 GB | 12.0 GB | 9.0 GB | +5.5 GB |
| Q6_K | 8.3 GB | 9.8 GB | 7.0 GB | +7.7 GB |
| Q5_K_M | 7.3 GB | 8.8 GB | 6.1 GB | +8.7 GB |
| Q5_K_S | 7.1 GB | 8.6 GB | 5.9 GB | +8.9 GB |
| Q4_1 | 6.6 GB | 8.1 GB | 5.4 GB | +9.4 GB |
| Q4_K_M | 6.4 GB | 7.9 GB | 5.2 GB | +9.6 GB |
| Q4_K_S | 6.1 GB | 7.6 GB | 5.0 GB | +9.9 GB |
| Q4_0 | 6.0 GB | 7.5 GB | 4.9 GB | +10.0 GB |
| Q3_K_M | 4.7 GB | 6.2 GB | 4.2 GB | +11.3 GB |
| Q3_K_S | 4.4 GB | 5.9 GB | 3.9 GB | +11.6 GB |
| Q2_K | 3.9 GB | 5.4 GB | 3.4 GB | +12.1 GB |
Try it in the cloud first
Don't want to download Ministral 3 8B 2512 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.
Advertisement
Full model details
Ministral 3 8B 2512 →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA RTX 5080 →
Top-ranked open-source models that fit in 16.0GB.
FAQ
Can the NVIDIA RTX 5080 run Ministral 3 8B 2512?
Yes. The NVIDIA RTX 5080's 16.0GB of VRAM is enough to run Ministral 3 8B 2512 at Q8_0 quantization (10.5GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 16.0GB. It uses about 10.5GB of memory and 12.0GB 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.