Mistralai Mistral Small Instruct 2409 speed on RTX 4090 and quantization-level VRAM fit.
RTX 4090 meets the minimum VRAM requirement for Q4 inference of Mistralai Mistral Small Instruct 2409. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4090 can run Mistralai Mistral Small Instruct 2409 with Q4 quantization. At approximately 63 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 4GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 20GB | 24GB | 63.00 tok/s | ✅ Fits comfortably |
| Q8 | 40GB | 24GB | 44.10 tok/s | ❌ Not recommended |
| FP16 | 80GB | 24GB | 23.94 tok/s | ❌ Not recommended |
Check current pricing links for RTX 4090 and similar cards.
Open RTX 4090 buy links →Use workload-focused recommendations before committing to a purchase.
Browse best GPU guides →Compare complete systems if you want ready-to-run hardware.
Compare prebuilt systems →RTX 4090 can run Mistralai Mistral Small Instruct 2409 at Q4 with an estimated 63 tok/s.
Q4 inference is estimated to need about 20GB 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.