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Project comparison
Xgboost vs Ultralytics
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Best matched with other framework tools.
28.6K
Stars
+227
Weekly
57/100
Health
Ultralytics
Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Best matched with other framework tools.
59.7K
Stars
+2.7K
Weekly
95/100
Health
Quick Take
Adoption
Ultralytics has the larger GitHub footprint with 59.7K stars.
Momentum
Ultralytics is currently growing faster at +2.7K stars this week.
Maintenance
Ultralytics has the stronger automated maintenance signal at 95/100. This is not a security or fit verdict.
Side-by-side evidence
Use these signals to narrow your choice, then confirm setup, license, and fit upstream.
| Signal | Xgboost | Ultralytics |
|---|---|---|
| Evidence status | Basic listing· 2026-10-04 09:18 UTC | Basic listing· 2026-10-04 09:17 UTC |
| GitHub stars | 28.6K | 59.7K |
| Weekly growth | +227 | +2.7K |
| Health score | Watch57/100 | Strong95/100 |
| Contributors | 692 | 407 |
| Commits per week | 6.8 | 50.8 |
| Open issues | 431 | 160 |
| Language | C++ | Python |
| License | Apache-2.0 | AGPL-3.0 |
| Last commit | 2026-07-22 11:00 UTC | 2026-07-22 16:13 UTC |
| Last release | v3.3.0 | v8.4.104 |
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