NVIDIA · GPU · Results: 26Q3, recorded 2026-09-06
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP32 | 565.29 |
| MobileNetV3 | BF16 | 313.42 |
| Flan-T5 Small | FP32 | 765.71 |
| Flan-T5 Small | BF16 | 456.20 |
| DistilGPT2 | FP32 | 728.59 |
| DistilGPT2 | BF16 | 402.79 |
| DistilBERT | FP32 | 930.51 |
| DistilBERT | BF16 | 736.92 |
| GraphGPS (Peptides) | FP32 | 273.57 |
| GraphGPS (Peptides) | BF16 | 280.73 |
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP16 | 2622.46 |
| MobileNetV3 | INT8 | 663.92 |
| Flan-T5 Small | FP16 | 2079.21 |
| Flan-T5 Small | INT8 | 1127.07 |
| Flan-T5 Small | FP8 | 1153.78 |
| DistilGPT2 | FP16 | 1176.82 |
| DistilGPT2 | INT8 | 706.70 |
| DistilGPT2 | FP8 | 709.12 |
| DistilBERT | FP16 | 1485.98 |
| DistilBERT | INT8 | 922.77 |
| DistilBERT | FP8 | 980.32 |
| GraphGPS (Peptides) | FP16 | 537.23 |
| GraphGPS (Peptides) | INT8 | 289.02 |
| GraphGPS (Peptides) | FP8 | 276.63 |
| Model | Precision | Sustained |
|---|---|---|
| Dense MatMul | FP32 | 357.86 |
| Dense MatMul | FP16 | 421.58 |
| Dense MatMul | BF16 | 427.53 |
| Dense MatMul | FP64 | 10.14 |
| Sparse MatMul | FP32 | 301.70 |
| Sparse MatMul | FP64 | 211.94 |
Results: 26Q3 · GT = LynxBenchAI Global Score. Every precision result is sustained throughput under a declared, bounded optimisation budget — no collapsed single number below the category level.
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