Alibaba Nlp Gte Qwen2 1.5B Instruct speed on Intel Arc B570 and quantization-level VRAM fit.
Intel Arc B570 meets the minimum VRAM requirement for Q4 inference of Alibaba Nlp Gte Qwen2 1.5B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
Intel Arc B570 can run Alibaba Nlp Gte Qwen2 1.5B Instruct with Q4 quantization. At approximately 75 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 9GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 10GB | 74.57 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 10GB | 52.20 tok/s | ✅ Fits comfortably |
| FP16 | 3GB | 10GB | 28.34 tok/s | ✅ Fits comfortably |
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Intel Arc B570 can run Alibaba Nlp Gte Qwen2 1.5B Instruct at Q4 with an estimated 75 tok/s.
Q4 inference is estimated to need about 1GB VRAM on this page, while Intel Arc B570 has 10GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.