Ilyagusev Saiga Llama3 8B speed on RX 7900 XTX and quantization-level VRAM fit.
RX 7900 XTX 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.
RX 7900 XTX can run Ilyagusev Saiga Llama3 8B with Q4 quantization. At approximately 109 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 19GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 5GB | 24GB | 109.08 tok/s | ✅ Fits comfortably |
| Q8 | 9GB | 24GB | 76.36 tok/s | ✅ Fits comfortably |
| FP16 | 17GB | 24GB | 41.45 tok/s | ✅ Fits comfortably |
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RX 7900 XTX can run Ilyagusev Saiga Llama3 8B at Q4 with an estimated 109 tok/s.
Q4 inference is estimated to need about 5GB VRAM on this page, while RX 7900 XTX has 24GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.