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RTX 5090 benchmark on coco val2017; readme guidance update #23

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dataplayer12 merged 1 commit into from
Jun 15, 2026
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RTX 5090 benchmark on coco val2017; readme guidance update #23

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5 changes: 3 additions & 2 deletions README.md
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Expand Up @@ -38,6 +38,7 @@ The numbers show end to end image processing latency per image (4K resolution) i
| Jetson Thor | | | | Please contribute |
| DGX Spark | | | | Please contribute |
| RTX 3090 | 438 ms | 75 ms | 5.82x | |
| RTX 5090 | 120.9 ms | 24.8 ms | 4.88x | COCO val2017, TRT 10.14.1 |
| A10 | 545.3 ms | 161.1 | 3.38x | GPU hits 100% utilization |
| A100 | 314.1 ms | 48.8 ms | 6.43x | 40GB SXM4 variant |
| H100 | 265.3 ms | 34.6 ms | 7.66x | PCIe variant |
Expand Down Expand Up @@ -112,11 +113,11 @@ docker run -it --rm \
```bash
python python/onnxexport.py
```
This produces `onnx_weights/sam3_static.onnx` plus external weight shards.
This produces `onnx_weights/sam3_dynamic.onnx` plus external weight shards.

5) Build a TensorRT engine
```bash
trtexec --onnx=onnx_weights/sam3_static.onnx --saveEngine=sam3_fp16.plan --fp16 --verbose
trtexec --onnx=onnx_weights/sam3_dynamic.onnx --saveEngine=sam3_fp16.plan --fp16 --verbose
```

6) Build the C++/CUDA library and sample app
Expand Down