Computer vision model weights, free download

How to load these weights

Install the Ultralytics package, then point the loader at the checkpoint. It downloads automatically on first use, or you can pass the local path to the file you downloaded above.

pip install ultralytics

from ultralytics import YOLO

# Downloads on first use, or pass a local path to your .pt file
model = YOLO("yolo11n.pt")
results = model("image.jpg")

Every model family

Jump straight to any family for its full write-up, FAQ and download table.

• YOLO26 weights
• YOLO11 weights
• YOLOv10 weights
• YOLOv9 weights
• YOLOv8 weights
• YOLOv5 (v5u) weights
• RT-DETR weights
• YOLO-World weights
• SAM 2.1 weights
• SAM weights
• MobileSAM weights
• FastSAM weights

Frequently asked questions

Are these computer-vision model weights free to download?

Yes. Every checkpoint here links to the official, publicly hosted weight file, with no sign-up. What differs is the license you may use them under: most Ultralytics YOLO weights are AGPL-3.0 (free for open-source, needs an Enterprise license for closed commercial use), while SAM, SAM 2.1, MobileSAM and RT-DETR are Apache-2.0. Always check the license badge before shipping.

How do I download YOLO, SAM or RT-DETR weights here?

Find the model in the table, then click the Download button on the variant you want. We first verify the file is available and then start the download straight from the official CDN, showing a confirmation popup, or the exact error if something goes wrong. You can also copy the filename and let the Ultralytics library fetch it automatically on first use.

What is a .pt file and how do I load it?

A .pt file is a PyTorch checkpoint containing the trained model weights. For any Ultralytics-ecosystem model you can load it in two lines: `from ultralytics import YOLO` then `model = YOLO("yolo11n.pt")`. On first use the library also downloads the file automatically, so the direct links here are for offline installs, air-gapped machines and mirroring.

Which model weights should I download for my project?

For general object detection start with YOLO11n or YOLO26n: small, fast, well-supported. Need commercial-friendly licensing? Use RT-DETR or SAM 2.1 (Apache-2.0). Need to segment or track anything from a prompt? Use SAM 2.1, or MobileSAM and FastSAM for the edge. Detect classes by text with no training? Use YOLO-World. The nano (n) or tiny variant is almost always the right first download.

What accuracy do these numbers represent?

For the detectors, the score is COCO val2017 mAP50-95 at the input size listed, as published by each model's own authors, not a benchmark re-run on this site. Cross-family numbers are indicative of tier, not a controlled head-to-head, because the families use different size ladders and training recipes. The Segment Anything models are promptable, so we list parameters and download size instead of a single accuracy figure.

Do I need internet access to use these after downloading?

No. Once you have the .pt file locally you can point the loader at the file path and run fully offline, which is exactly why these direct links exist. Weights are self-contained; only the first download needs a connection.