Petals Team Stablebeluga2 speed on NVIDIA A5000 and quantization-level VRAM fit.
NVIDIA A5000 meets the minimum VRAM requirement for Q4 inference of Petals Team Stablebeluga2. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA A5000 can run Petals Team Stablebeluga2 with Q4 quantization. At approximately 150 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 23GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 24GB | 150.43 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 24GB | 105.30 tok/s | ✅ Fits comfortably |
| FP16 | 4GB | 24GB | 57.16 tok/s | ✅ Fits comfortably |
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NVIDIA A5000 can run Petals Team Stablebeluga2 at Q4 with an estimated 150 tok/s.
Q4 inference is estimated to need about 1GB VRAM on this page, while NVIDIA A5000 has 24GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.