Swiss AI Apertus 8B Instruct 2509 speed on NVIDIA L4 and quantization-level VRAM fit.
NVIDIA L4 meets the minimum VRAM requirement for Q4 inference of Swiss AI Apertus 8B Instruct 2509. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA L4 can run Swiss AI Apertus 8B Instruct 2509 with Q4 quantization. At approximately 61 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 20GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 4GB | 24GB | 60.57 tok/s | ✅ Fits comfortably |
| Q8 | 8GB | 24GB | 42.40 tok/s | ✅ Fits comfortably |
| FP16 | 16GB | 24GB | 23.02 tok/s | ✅ Fits comfortably |
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Browse best GPU guides →Compare complete systems if you want ready-to-run hardware.
Compare prebuilt systems →NVIDIA L4 can run Swiss AI Apertus 8B Instruct 2509 at Q4 with an estimated 61 tok/s.
Q4 inference is estimated to need about 4GB VRAM on this page, while NVIDIA L4 has 24GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.