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Parameters
12.2M
FLOPs
32.8G
Input Size
640px
License
Apache-2.0
Architecture
Type
one-stage
Backbone
NAS-Optimized
Neck
QSP
Head
Decoupled
Benchmark Results
Performance on COCO val2017 across different hardware configurations
| Hardware | mAP@50-95 | FPS | Latency | VRAM |
|---|---|---|---|---|
| NVIDIA A100 (TensorRT FP16) | 47.6% | 144.5 | 6.9ms | 527 MB |
| NVIDIA T4 (TensorRT FP16) | 47.4% | 60.3 | 16.6ms | 566 MB |
| CPU (ONNX Runtime) | 47.6% | 6.8 | 147.0ms | 557 MB |
Speed Breakdown (A100 TensorRT)
End-to-end latency breakdown showing preprocessing, inference, and postprocessing times
1.2ms
3.1ms
2.6ms
Preprocess
Inference
Postprocess (NMS)
Usage with LibreYOLO
from libreyolo import YOLO
# Load model
model = YOLO.from_pretrained("https://huggingface.co/Libre-YOLO/yolo-nas-s")
# Run inference
results = model.predict("image.jpg")
# Process results
for box in results.boxes:
print(f"Class: {box.cls}, Confidence: {box.conf:.2f}")nas-optimizedefficient
Notes
Neural Architecture Search designed by Deci AI
Related Models (yolo-nas)