Ilyagusev Saiga Llama3 8B speed on NVIDIA L4 and quantization-level VRAM fit.
NVIDIA L4 meets the minimum VRAM requirement for Q4 inference of Ilyagusev Saiga Llama3 8B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA L4 can run Ilyagusev Saiga Llama3 8B with Q4 quantization. At approximately 61 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 22GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 2GB | 24GB | 60.57 tok/s | ✅ Fits comfortably |
| Q8 | 4GB | 24GB | 42.40 tok/s | ✅ Fits comfortably |
| FP16 | 8GB | 24GB | 23.02 tok/s | ✅ Fits comfortably |
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Open NVIDIA L4 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 →NVIDIA L4 can run Ilyagusev Saiga Llama3 8B at Q4 with an estimated 61 tok/s.
Q4 inference is estimated to need about 2GB 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.