Yolo V8 Download Apr 2026

from ultralytics import YOLO model = YOLO('yolov8n.pt') # Downloads to current directory or ~/.cache/ultralytics/ Download the desired weight file directly from the official Ultralytics release assets:

Execute the following Python code. The system will automatically fetch the default Nano model ( yolov8n.pt ): yolo v8 download

https://github.com/ultralytics/assets/releases/download/v0.0.0/[FILENAME].pt from ultralytics import YOLO model = YOLO('yolov8n

Example for Large model: https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l.pt To confirm the installation and weights are functioning, run a test inference: For users who need to modify the source

pip install ultralytics Verification: This command downloads the core library and its dependencies (Torch, NumPy, OpenCV). No model weights are downloaded at this stage. For users who need to modify the source code or contribute to the project.

| Model Type | File Name | Size (MB) | Use Case | | :--------- | :----------- | :-------- | :-------------------------------- | | Nano | yolov8n.pt | 6.2 | Mobile/Edge devices, speed first | | Small | yolov8s.pt | 21.4 | Balanced speed/accuracy | | Medium | yolov8m.pt | 49.6 | General purpose | | Large | yolov8l.pt | 83.7 | High accuracy, slower | | Extra-Large| yolov8x.pt | 130.5 | Maximum accuracy |

from ultralytics import YOLO import cv2 model = YOLO('yolov8n.pt') Run inference on a sample image results = model('https://ultralytics.com/images/bus.jpg') Display results for r in results: r.show() # Opens image window