NVIDIA · GPU · Results: 26Q3, recorded 2026-10-06
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP32 | 342.30 |
| MobileNetV3 | BF16 | 252.36 |
| Flan-T5 Small | FP32 | 474.94 |
| Flan-T5 Small | BF16 | 260.10 |
| DistilGPT2 | FP32 | 383.61 |
| DistilGPT2 | BF16 | 215.88 |
| DistilBERT | FP32 | 527.44 |
| DistilBERT | BF16 | 391.85 |
| GraphGPS (Peptides) | FP32 | 190.84 |
| GraphGPS (Peptides) | BF16 | 180.11 |
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP16 | 1354.41 |
| MobileNetV3 | INT8 | 390.30 |
| Flan-T5 Small | FP16 | 929.96 |
| Flan-T5 Small | INT8 | 537.06 |
| Flan-T5 Small | FP8 | 674.11 |
| DistilGPT2 | FP16 | 680.11 |
| DistilGPT2 | INT8 | 433.61 |
| DistilGPT2 | FP8 | 456.92 |
| DistilBERT | FP16 | 782.83 |
| DistilBERT | INT8 | 457.85 |
| DistilBERT | FP8 | 522.97 |
| GraphGPS (Peptides) | FP16 | 257.99 |
| GraphGPS (Peptides) | INT8 | 137.62 |
| GraphGPS (Peptides) | FP8 | 135.74 |
| Model | Precision | Sustained |
|---|---|---|
| Dense MatMul | FP32 | 221.64 |
| Dense MatMul | FP16 | 229.28 |
| Dense MatMul | BF16 | 245.25 |
| Dense MatMul | FP64 | 8.52 |
| Sparse MatMul | FP32 | 603.26 |
| Sparse MatMul | FP64 | 640.06 |
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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