#44th of 7 in ML frameworks and libraries
ultralytics
Python library and CLI for training and running YOLO vision models
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- Stars
- 62.5k
- License
- AGPL-3.0
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Python
Checked on GitHub.
Overview
Ultralytics provides the `ultralytics` Python package and `yolo` CLI for training, validating, predicting, tracking and exporting YOLO models. Tasks include detection, instance and semantic segmentation, depth estimation, classification, pose and oriented boxes. Pretrained YOLO26 weights download on first use, and models export to formats such as ONNX.
Who it is for: Engineers building object detection and video analysis pipelines
Strengths
- One package and CLI cover train, val, predict, track and export across seven vision tasks
- Pretrained YOLO26 n/s/m/l/x weights with published COCO mAP and CPU/T4 latency tables
- Supports older YOLO versions back to YOLOv3, plus export to ONNX
- Install via pip, Conda or Docker; docs in multiple languages
Weaknesses
- AGPL-3.0 license; commercial use needs a paid Enterprise License
- Vision only; no LLM or language model support
- Pretrained weights download from Ultralytics releases at first use
- YOLO27 is announced but unavailable, with no launch date
What it needs
- GPU optional
- Docker
- Needs Python>=3.8, PyTorch>=1.8
- Models: YOLO26, YOLOv3, ONNX export, TensorRT export
Head to head
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