Can I Run Ministral 3 3B on a NVIDIA RTX PRO 6000 Blackwell?
Runs at full precision (f32). Zero quality loss.
14 quantizations fit your 96.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| f32BEST | 13.0 GB | 14.5 GB | 1.7 GB | +83.0 GB |
| fp16 | 7.0 GB | 8.5 GB | 0.8 GB | +89.0 GB |
| Q8_0 | 4.2 GB | 5.7 GB | 3.6 GB | +91.8 GB |
| Q6_K | 3.5 GB | 5.0 GB | 2.8 GB | +92.5 GB |
| Q5_K_M | 3.1 GB | 4.6 GB | 2.5 GB | +92.9 GB |
| Q5_K_S | 3.1 GB | 4.6 GB | 2.4 GB | +92.9 GB |
| Q4_1 | 2.9 GB | 4.4 GB | 2.2 GB | +93.1 GB |
| Q4_K_M | 2.8 GB | 4.3 GB | 2.1 GB | +93.2 GB |
| Q4_K_S | 2.7 GB | 4.2 GB | 2.0 GB | +93.3 GB |
| Q4_0 | 2.7 GB | 4.2 GB | 2.0 GB | +93.3 GB |
| Q3_K_L | 2.3 GB | 3.8 GB | 1.9 GB | +93.7 GB |
| Q3_K_M | 2.3 GB | 3.8 GB | 1.8 GB | +93.7 GB |
| Q3_K_S | 2.2 GB | 3.7 GB | 1.6 GB | +93.8 GB |
| Q2_K | 2.0 GB | 3.5 GB | 1.5 GB | +94.0 GB |
Try it in the cloud first
Don't want to download Ministral 3 3B 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 96.0GB.
FAQ
Can the NVIDIA RTX PRO 6000 Blackwell run Ministral 3 3B?
Yes. The NVIDIA RTX PRO 6000 Blackwell's 96.0GB of VRAM is enough to run Ministral 3 3B at f32 quantization (13.0GB required).
What's the best quantization to use?
f32 is the highest-precision quantization that fits in your 96.0GB. It uses about 13.0GB of memory and 14.5GB 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.