NVIDIA · GPU · Results: 26Q3, recorded 2026-08-13
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP32 | 537.67 |
| MobileNetV3 | BF16 | 243.47 |
| Flan-T5 Small | FP32 | 898.75 |
| Flan-T5 Small | BF16 | 523.52 |
| DistilGPT2 | FP32 | 903.48 |
| DistilGPT2 | BF16 | 522.66 |
| DistilBERT | FP32 | 1081.01 |
| DistilBERT | BF16 | 940.17 |
| GraphGPS (Peptides) | FP32 | 318.48 |
| GraphGPS (Peptides) | BF16 | 357.80 |
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP16 | 2187.52 |
| MobileNetV3 | INT8 | 692.80 |
| Flan-T5 Small | FP16 | 2327.68 |
| Flan-T5 Small | INT8 | 947.28 |
| Flan-T5 Small | FP8 | 1356.97 |
| DistilGPT2 | FP16 | 2084.27 |
| DistilGPT2 | INT8 | 954.30 |
| DistilGPT2 | FP8 | 1194.18 |
| DistilBERT | FP16 | 1714.39 |
| DistilBERT | INT8 | 720.85 |
| DistilBERT | FP8 | 912.88 |
| GraphGPS (Peptides) | FP16 | 748.98 |
| GraphGPS (Peptides) | INT8 | 341.34 |
| GraphGPS (Peptides) | FP8 | 368.62 |
| Model | Precision | Sustained |
|---|---|---|
| Dense MatMul | FP32 | 706.80 |
| Dense MatMul | FP16 | 696.38 |
| Dense MatMul | BF16 | 715.56 |
| Dense MatMul | FP64 | 240.90 |
| Sparse MatMul | FP32 | 143.02 |
| Sparse MatMul | FP64 | 254.53 |
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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