Ilyagusev Saiga Llama3 8B speed on RTX 5090 and quantization-level VRAM fit.
RTX 5090 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.
RTX 5090 can run Ilyagusev Saiga Llama3 8B with Q4 quantization. At approximately 300 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 30GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 2GB | 32GB | 299.77 tok/s | ✅ Fits comfortably |
| Q8 | 4GB | 32GB | 209.84 tok/s | ✅ Fits comfortably |
| FP16 | 8GB | 32GB | 113.91 tok/s | ✅ Fits comfortably |
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Open RTX 5090 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 5090 can run Ilyagusev Saiga Llama3 8B at Q4 with an estimated 300 tok/s.
Q4 inference is estimated to need about 2GB VRAM on this page, while RTX 5090 has 32GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.