NVIDIA · GPU · Results: 26Q3, recorded 2026-09-06
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP32 | 363.86 |
| MobileNetV3 | BF16 | 175.17 |
| Flan-T5 Small | FP32 | 657.00 |
| Flan-T5 Small | BF16 | 353.74 |
| DistilGPT2 | FP32 | 657.14 |
| DistilGPT2 | BF16 | 358.79 |
| DistilBERT | FP32 | 805.46 |
| DistilBERT | BF16 | 690.91 |
| GraphGPS (Peptides) | FP32 | 225.70 |
| GraphGPS (Peptides) | BF16 | 230.04 |
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP16 | 1709.26 |
| MobileNetV3 | INT8 | 503.53 |
| Flan-T5 Small | FP16 | 1645.66 |
| Flan-T5 Small | INT8 | 759.30 |
| Flan-T5 Small | FP8 | 0.00 |
| DistilGPT2 | FP16 | 1607.95 |
| DistilGPT2 | INT8 | 727.01 |
| DistilGPT2 | FP8 | 0.00 |
| DistilBERT | FP16 | 1267.42 |
| DistilBERT | INT8 | 613.96 |
| DistilBERT | FP8 | 0.00 |
| GraphGPS (Peptides) | FP16 | 548.43 |
| GraphGPS (Peptides) | INT8 | 272.75 |
| GraphGPS (Peptides) | FP8 | 0.00 |
| Model | Precision | Sustained |
|---|---|---|
| Dense MatMul | FP32 | 312.37 |
| Dense MatMul | FP16 | 431.41 |
| Dense MatMul | BF16 | 477.39 |
| Dense MatMul | FP64 | 132.43 |
| Sparse MatMul | FP32 | 91.46 |
| Sparse MatMul | FP64 | 163.00 |
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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