Vikhyatk Moondream2 speed on RX 7900 GRE and quantization-level VRAM fit.
RX 7900 GRE meets the minimum VRAM requirement for Q4 inference of Vikhyatk Moondream2. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RX 7900 GRE can run Vikhyatk Moondream2 with Q4 quantization. At approximately 109 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 15GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 16GB | 109.45 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 16GB | 76.61 tok/s | ✅ Fits comfortably |
| FP16 | 4GB | 16GB | 41.59 tok/s | ✅ Fits comfortably |
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RX 7900 GRE can run Vikhyatk Moondream2 at Q4 with an estimated 109 tok/s.
Q4 inference is estimated to need about 1GB VRAM on this page, while RX 7900 GRE has 16GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.