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Baseus Bowie MC2 Air vs Wavefun FitBuds: which should you buy?

Specs, scores and condensed review verdicts for the Baseus Bowie MC2 Air vs Wavefun FitBuds, side by side. Where a product has no HearWiki score yet, not enough reviews have been aggregated to rate it.

Score breakdown

Each axis is a 0–10 blend of what reviewers scored, not a lab measurement.

Baseus Bowie MC2 Air
Sound7.5
Battery8.0
Calls6.5
Value9.0
Wavefun FitBuds

No sub-scores yet - not enough rated reviews.

Specifications

Specification comparison of Baseus Bowie MC2 Air vs Wavefun FitBuds
SpecBaseus Bowie MC2 AirWavefun FitBuds
TypeOpen-EarOpen-Ear
Price (USD)$35$29
HearWiki score78 / 100 · GreatNot scored
Released20252022
Audio
Driver11 mm dynamic driver11mm dynamic
Driver size11 mm-
Drivers per side1-
Frequency response20Hz-20kHz-
Impedance14 Ω16 Ω
Wireless
Bluetooth6.05.3
Bluetooth version6.0-
CodecsSBC, AAC, LDACAAC
Multipoint pairingYes-
Latency38 ms-
Wireless range10 m-
Battery
Battery life11.5 h15 h
Battery incl. case49 h-
Full charge time120 min-
Wireless chargingNo-
Features
Active noise cancellingNo-
Design
Weight2 g108.9 g
Water resistanceIP67-
USB-CYes-
Model code-Wavefun XBuds
Calls
Microphones4-

What reviewers said

Baseus Bowie MC2 Air

The Baseus Bowie MC2 Air are budget-friendly open-ear clip earbuds that deliver a surprisingly full sound and a secure, comfortable fit for workouts. They pack a strong feature set for the price, including Bluetooth 6.0, LDAC support, multipoint connectivity, and IP67 water resistance, though they lack active noise cancellation and wireless charging. Call quality in windy conditions is a noted weak spot, but overall they offer excellent value for the money.

  • Pro:Secure and comfortable clip-on fit for active use
  • Pro:Full, unexpected sound quality for an open-ear design
  • Pro:Bluetooth 6.0 with LDAC and multipoint support
  • Con:Call quality suffers in windy conditions
  • Con:No active noise cancellation
  • Con:No wireless charging support

Wavefun FitBuds

No summary yet - we haven't aggregated enough reviews.

Summaries are AI-condensed and paraphrased from published reviews and specs - not original hands-on testing. More on our method.

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