NVIDIA · GPU · Results: 26Q3, recorded 2026-09-24
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP32 | 275.56 |
| MobileNetV3 | BF16 | 187.82 |
| Flan-T5 Small | FP32 | 304.29 |
| Flan-T5 Small | BF16 | 175.08 |
| DistilGPT2 | FP32 | 282.37 |
| DistilGPT2 | BF16 | 171.86 |
| DistilBERT | FP32 | 363.76 |
| DistilBERT | BF16 | 283.55 |
| GraphGPS (Peptides) | FP32 | 102.22 |
| GraphGPS (Peptides) | BF16 | 100.34 |
| Model | Precision | Sustained |
|---|---|---|
| MobileNetV3 | FP16 | 1030.82 |
| MobileNetV3 | INT8 | 284.97 |
| Flan-T5 Small | FP16 | 817.17 |
| Flan-T5 Small | INT8 | 399.33 |
| Flan-T5 Small | FP8 | 532.48 |
| DistilGPT2 | FP16 | 540.65 |
| DistilGPT2 | INT8 | 339.70 |
| DistilGPT2 | FP8 | 346.52 |
| DistilBERT | FP16 | 599.11 |
| DistilBERT | INT8 | 347.48 |
| DistilBERT | FP8 | 383.99 |
| GraphGPS (Peptides) | FP16 | 226.60 |
| GraphGPS (Peptides) | INT8 | 108.33 |
| GraphGPS (Peptides) | FP8 | 113.94 |
| Model | Precision | Sustained |
|---|---|---|
| Dense MatMul | FP32 | 125.68 |
| Dense MatMul | FP16 | 165.83 |
| Dense MatMul | BF16 | 166.21 |
| Dense MatMul | FP64 | 4.85 |
| Sparse MatMul | FP32 | 428.80 |
| Sparse MatMul | FP64 | 396.02 |
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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