Dyson V12 Detect Slim vs Dyson V10 Konical

Quick take: The Dyson V10 Konical costs $120 less.

SpecDyson V12 Detect SlimDyson V10 Konical
Price~$620~$500
TypeCordless StickCordless Stick
Suction150 AW150 AW
Battery60 min60 min
Navigation
FiltrationWhole-machine HEPA-sealedWhole-machine HEPA-sealed
CordlessYesYes
BaggedNoNo
Noise
Dustbin0.35 L
Water tank
Self-empty dockNoNo
Auto mop washingNoNo
Hot water washingNoNo
Obstacle avoidanceNoNo
Carpet detectionNoNo
Auto mop liftingNoNo
Multi-floor mappingNoNo
App controlNoNo
Dimensions
Weight5.2 lbs5.75 lbs
Warranty2 years2 years

Pros & cons

Dyson V12 Detect Slim

  • 5.2 lbs makes daily and above-floor cleaning genuinely easy
  • Laser dust illumination and piezo particle counter carried over from the V15
  • Power button instead of a hold-down trigger
  • Click-in battery is removable and replaceable
  • Long-term owners report the light weight keeps it in daily use where heavier sticks sat idle
  • Whole-machine HEPA filtration at a lower price than the flagships
  • 150AW is well below the V15/Gen5 — weaker on thick carpet
  • 0.35L bin is small; expect multiple empties per whole-house clean
  • Owners report battery capacity declines noticeably after ~3 years of heavy use
  • Head is narrower than the flagships, so big rooms take longer
  • No app or smart connectivity

Dyson V10 Konical

  • Conical brush bars specifically engineered against long-hair wrap
  • All Floors Cones head illuminates dust and adapts to hard floor and carpet
  • Auto-empty Dok option (sold separately) is Dyson's first self-emptying cordless dock
  • Cheaper than the V11/V15/Gen5 lines while sharing the same de-tangling design language
  • 60-minute max runtime
  • 150AW suction is noticeably below the V11 (185AW) and V15/Gen5 (240-250AW) lines
  • Auto-empty Dok is a separate purchase, not included at this price
  • No laser dust reveal or particle sensor
  • Manufacturer-published dustbin capacity not listed on the pages found during research
  • New enough (2026) that independent long-term reliability data is still thin