NVIDIA · GPU · Results: 26Q3, recorded 2026-09-24
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP32 | 321.34 |
| MobileNetV3 | BF16 | 215.50 |
| Flan-T5 Small | FP32 | 359.22 |
| Flan-T5 Small | BF16 | 203.49 |
| DistilGPT2 | FP32 | 327.51 |
| DistilGPT2 | BF16 | 192.02 |
| DistilBERT | FP32 | 430.72 |
| DistilBERT | BF16 | 322.97 |
| GraphGPS (Peptides) | FP32 | 121.12 |
| GraphGPS (Peptides) | BF16 | 121.58 |
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP16 | 1082.65 |
| MobileNetV3 | INT8 | 305.45 |
| Flan-T5 Small | FP16 | 972.75 |
| Flan-T5 Small | INT8 | 472.69 |
| Flan-T5 Small | FP8 | 662.35 |
| DistilGPT2 | FP16 | 681.78 |
| DistilGPT2 | INT8 | 428.57 |
| DistilGPT2 | FP8 | 436.57 |
| DistilBERT | FP16 | 733.51 |
| DistilBERT | INT8 | 404.01 |
| DistilBERT | FP8 | 461.01 |
| GraphGPS (Peptides) | FP16 | 248.92 |
| GraphGPS (Peptides) | INT8 | 117.43 |
| GraphGPS (Peptides) | FP8 | 126.93 |
| Model | Precision | Sustained |
|---|---|---|
| Dense MatMul | FP32 | 192.95 |
| Dense MatMul | FP16 | 194.26 |
| Dense MatMul | BF16 | 194.08 |
| Dense MatMul | FP64 | 4.87 |
| Sparse MatMul | FP32 | 608.42 |
| Sparse MatMul | FP64 | 498.30 |
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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