Mistralai Ministral 3 14B Instruct 2512 speed on RTX 4090 and quantization-level VRAM fit.
RTX 4090 meets the minimum VRAM requirement for Q4 inference of Mistralai Ministral 3 14B Instruct 2512. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4090 can run Mistralai Ministral 3 14B Instruct 2512 with Q4 quantization. At approximately 135 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 17GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 7GB | 24GB | 135.00 tok/s | ✅ Fits comfortably |
| Q8 | 14GB | 24GB | 94.50 tok/s | ✅ Fits comfortably |
| FP16 | 28GB | 24GB | 51.30 tok/s | ❌ Not recommended |
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Compare prebuilt systems →RTX 4090 can run Mistralai Ministral 3 14B Instruct 2512 at Q4 with an estimated 135 tok/s.
Q4 inference is estimated to need about 7GB VRAM on this page, while RTX 4090 has 24GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.