Model comparison · YOLOv10 vs YOLOv5 (v5u)

YOLOv10 vs YOLOv5 (v5u)

A size-tier-by-size-tier comparison of YOLOv10 and Ultralytics YOLOv5 (v5u): published COCO accuracy, parameter counts, licensing and which one to reach for. Every figure is the model authors' own, linked to its source.

CompareYOLOv10
AgainstYOLOv5 (v5u)
75%fewer params

mAP comparison

YOLOv10YOLOv5 (v5u)
31.037.644.350.957.5mAPNanoSmallMediumLargeExtra largeModel size tierYOLOv10n: 38.5 mAP, 2.3M paramsYOLOv10s: 46.3 mAP, 7.2M paramsYOLOv10m: 51.1 mAP, 15.4M paramsYOLOv10l: 53.2 mAP, 24.4M paramsYOLOv10x: 54.4 mAP, 29.5M paramsYOLOv5nu: 34.3 mAP, 2.6M paramsYOLOv5su: 43.0 mAP, 9.1M paramsYOLOv5mu: 49.0 mAP, 25.1M paramsYOLOv5lu: 52.2 mAP, 53.2M paramsYOLOv5xu: 53.2 mAP, 97.2M params

YOLOv10

  • Nano 38.5
  • Small 46.3
  • Medium 51.1
  • Large 53.2
  • Extra large 54.4

YOLOv5 (v5u)

  • Nano 34.3
  • Small 43.0
  • Medium 49.0
  • Large 52.2
  • Extra large 53.2
COCO mAP at 640px, as published by each model’s authors. The y axis spans 31.0 to 57.5 rather than starting at zero, so small differences stay visible. Points are the published checkpoints; the joining lines are for reading order only.

Accuracy and size, tier by tier

Each row pairs the equivalent rung of both size ladders, so the numbers sit side by side at comparable capacity. Every figure is the model authors’ own.

  • COCO mAP50-95 @ 640px
  • mAP: higher is better
  • Params (M): lower is better
YOLOv10 and YOLOv5 (v5u) compared at each size tier: published COCO mAP50-95 at 640px and parameter counts in millions.
TierYOLOv10YOLOv5 (v5u)Δ mAP
ModelmAPParamsModelmAPParams
NanoYOLOv10n38.52.3MYOLOv5nu34.32.6M+4.2
SmallYOLOv10s46.37.2MYOLOv5su43.09.1M+3.3
MediumYOLOv10m51.115.4MYOLOv5mu49.025.1M+2.1
LargeYOLOv10l53.224.4MYOLOv5lu52.253.2M+1.0
Extra largeYOLOv10x54.429.5MYOLOv5xu53.297.2M+1.2

Δ mAP is YOLOv10 minus YOLOv5 (v5u): positive means YOLOv10 is ahead at that tier. Sources: YOLOv10 docs · YOLOv10 paper · YOLOv5 (v5u) docs

YOLOv10 also ships YOLOv10b, which sits between the rungs above and has no direct counterpart in YOLOv5 (v5u), so it is left out of the paired rows rather than matched to an unequal one.

Additional information

  • YOLOv10 posts the higher published COCO mAP at all 5 matched size tiers, averaging 2.36 mAP ahead of YOLOv5 (v5u). The gap is widest at the nano tier, where YOLOv10 leads by 4.2 mAP. At the top of each range, YOLOv10 reaches 54.4 mAP against 53.2.

  • 75% fewer parameters, same accuracy. YOLOv10l reaches 53.2 mAP from 24.4M parameters, matching or beating YOLOv5xu at 53.2 mAP from 97.2M.

    Parameter count is not latency. It is a good proxy for download size and memory, but throughput depends on your hardware, batch size and export format, so measure on your own target.

YOLOv10

The first popular NMS-free, end-to-end YOLO.

Released
2024 · Tsinghua University (THU-MIG)
License
AGPL-3.0
Framework
Built on Ultralytics (PyTorch)
Tasks
Detect

The first widely used YOLO that skips the NMS post-processing step, using paired training heads so inference is truly end to end and low latency.

Download YOLOv10 weights →

YOLOv5 (v5u)

The classic that made YOLO easy to ship, retrained anchor-free.

Released
2020 · Ultralytics
License
AGPL-3.0
Framework
Ultralytics (PyTorch)
Tasks
Detect, Segment, Classify

The anchor-free v5u retrain of the classic PyTorch YOLO, keeping its easy training and export while adopting the newer YOLOv8 detection head for better accuracy.

Download YOLOv5 (v5u) weights →

YOLOv10 and YOLOv5 (v5u) against the whole lineage

YOLOv10 and YOLOv5 (v5u) against every other detector here, on one shared scale. The rest are dimmed; hover any row to bring it back.

Every YOLO detector in this section, with release year, publisher, published COCO mAP50-95 range at 640px, parameter-count range and licence.
ModelReleasedmAP rangeParams rangeLicence
YOLO26202640.9 to 57.52.4M to 55.7MAGPL-3.0
YOLO12202540.6 to 55.22.6M to 59.1MAGPL-3.0
YOLO11202439.5 to 54.72.6M to 56.9MAGPL-3.0
YOLOv10202438.5 to 54.42.3M to 29.5MAGPL-3.0
YOLOv9202438.3 to 55.62.0M to 58.1MGPL-3.0
YOLOv8202337.3 to 53.93.2M to 68.2MAGPL-3.0
YOLOv5 (v5u)202034.3 to 53.22.6M to 97.2MAGPL-3.0

Every matchup

YOLO26 vs YOLO12YOLO26 vs YOLO11YOLO26 vs YOLOv10YOLO26 vs YOLOv9YOLO26 vs YOLOv8YOLO26 vs YOLOv5 (v5u)YOLO12 vs YOLO11YOLO12 vs YOLOv10YOLO12 vs YOLOv9YOLO12 vs YOLOv8YOLO12 vs YOLOv5 (v5u)YOLO11 vs YOLOv10YOLO11 vs YOLOv9YOLO11 vs YOLOv8YOLO11 vs YOLOv5 (v5u)YOLOv10 vs YOLOv9YOLOv10 vs YOLOv8YOLOv10 vs YOLOv5 (v5u)YOLOv9 vs YOLOv8YOLOv9 vs YOLOv5 (v5u)YOLOv8 vs YOLOv5 (v5u)

Looking for the weights themselves? Download any of these checkpoints from the model-weights hub, or see how the trackers behind them compare in the YOLO tracker benchmarks.