NVIDIA · GPU · Results: 26Q3, recorded 2026-08-26
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP32 | 564.13 |
| MobileNetV3 | BF16 | 257.12 |
| Flan-T5 Small | FP32 | 1095.97 |
| Flan-T5 Small | BF16 | 622.63 |
| DistilGPT2 | FP32 | 1159.01 |
| DistilGPT2 | BF16 | 651.85 |
| DistilBERT | FP32 | 1480.99 |
| DistilBERT | BF16 | 1291.98 |
| GraphGPS (Peptides) | FP32 | 374.00 |
| GraphGPS (Peptides) | BF16 | 386.94 |
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP16 | 2832.98 |
| MobileNetV3 | INT8 | 931.43 |
| Flan-T5 Small | FP16 | 3919.63 |
| Flan-T5 Small | INT8 | 1389.31 |
| Flan-T5 Small | FP8 | 1658.94 |
| DistilGPT2 | FP16 | 3797.65 |
| DistilGPT2 | INT8 | 1489.31 |
| DistilGPT2 | FP8 | 1920.23 |
| DistilBERT | FP16 | 2611.72 |
| DistilBERT | INT8 | 1090.29 |
| DistilBERT | FP8 | 1362.71 |
| GraphGPS (Peptides) | FP16 | 1060.04 |
| GraphGPS (Peptides) | INT8 | 520.52 |
| GraphGPS (Peptides) | FP8 | 548.07 |
| Model | Precision | Sustained |
|---|---|---|
| Dense MatMul | FP32 | 1026.69 |
| Dense MatMul | FP16 | 1264.27 |
| Dense MatMul | BF16 | 1315.06 |
| Dense MatMul | FP64 | 414.37 |
| Sparse MatMul | FP32 | 161.05 |
| Sparse MatMul | FP64 | 280.45 |
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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