vision
YOLOv10
Tsinghua University (School of Software and Department of Automation) NMS-free YOLO detector; source of the NMS-free design used in YOLO26.
Levelmodel
Classvision
Parameters2.8M
Contextnot in the notes
ReleasedMay 2024
Opennessopen source
Runs onembedded GPU, single datacentre GPU
Statusactive
Lineage
successor
YOLO26 is a child (successor)low confidencenotesWhere this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 4 models. Confidence and evidence are the notes' own.
Identity
- Developer
- Tsinghua University
- Family
- not in the notes
- Released
- May 2024 sourcesannouncement page
- Weights published
- 1 Jun 2024
- Record checked
- 10 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- CNN NMS-free YOLO
- Total parameters
- 2.8M sources
- Active parameters
- –
- Checkpoint parameters
- –
- Note
- 2.80M parameters for the n variant (HF jameslahm/yolov10n)
- Context length
- not in the notes
- Input
- image
- Output
- image, text
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open source
- Licence
- GNU Affero General Public License v3.0 sources
- Access routes
- open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- embedded GPU, single datacentre GPU
- Footprint
- not in the notes
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Industry Use Cases
No industry use case links this model.
Links
DeveloperTsinghua Universityuniversity, China
Tsinghua Universityuniversity, ChinaModelYOLOv10Tsinghua University, vision
YOLOv10Tsinghua University, visionUse CasesSafety (PPE, Hazards, Fatigue)IndustrialVisual Quality Inspection and Defect DetectionIndustrialUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Bukit Asam TbkIn production, 9 Sep 2026
PT Aneka Tambang Tbk (ANTAM), ferronickelIn production, 9 Sep 2026PLN Indonesia Power with Huawei (PLTU Banten 3 Lontar)Research, 26 Nov 2025
PT Kilang Pertamina Internasional (Pertamina refineries)In production, 17 Oct 2025+5 moreDeployments of these use cases; none names this model.
PT Bukit Asam TbkIn production, 9 Sep 2026PT Aneka Tambang Tbk (ANTAM), ferronickelIn production, 9 Sep 2026PLN Indonesia Power with Huawei (PLTU Banten 3 Lontar)Research, 26 Nov 2025PT Kilang Pertamina Internasional (Pertamina refineries)In production, 17 Oct 2025+5 moreDeployments of these use cases; none names this model.Organisations 1
Sources
- YOLOv10: Real-Time End-to-End Object Detection arxiv.org https://arxiv.org/html/2405.14458
- huggingface.co/api/models/jameslahm/yolov10n https://huggingface.co/api/models/jameslahm/yolov10n
- Models Supported by Ultralytics | Ultralytics Docs docs.ultralytics.com https://docs.ultralytics.com/yolo/
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "YOLOv10", https://aurion.semai.id/models/tsinghua-university-yolov10/, records of October 2026.