Unsloth Meta Llama 3.1 8B Instruct Bnb 4bit speed on RTX 5080 and quantization-level VRAM fit.
RTX 5080 meets the minimum VRAM requirement for Q4 inference of Unsloth Meta Llama 3.1 8B Instruct Bnb 4bit. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 5080 can run Unsloth Meta Llama 3.1 8B Instruct Bnb 4bit with Q4 quantization. At approximately 158 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 12GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 4GB | 16GB | 158.10 tok/s | ✅ Fits comfortably |
| Q8 | 8GB | 16GB | 110.67 tok/s | ✅ Fits comfortably |
| FP16 | 16GB | 16GB | 60.08 tok/s | ⚠️ Tight fit |
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Compare prebuilt systems →RTX 5080 can run Unsloth Meta Llama 3.1 8B Instruct Bnb 4bit at Q4 with an estimated 158 tok/s.
Q4 inference is estimated to need about 4GB VRAM on this page, while RTX 5080 has 16GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.