CVJ Mermaid II Review: Ranked #262 of 1448

Last updated: October 20, 2026

The CVJ Mermaid II ranks #262 out of 1448 total In-Ear Headphones for sound quality. See all Headphones rankings for every top pick.

Brand: CVJ

Prices on this page were last checked October 20, 2026 at 10:35 PM UTC. Product prices and availability are accurate as of that date/time and are subject to change; the price and availability shown on Amazon at the time of purchase will apply to the purchase of this product.

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#262 CVJ Mermaid II: $99.99 Amazon $99.99 eBay

Older model: the R2E3 Mermaid (ranked lower, rated 3.1/5). See every R2E3 and CVJ Mermaid generation.

Pros: A single 10 mm dynamic driver earphone measured by two reviewers, whose bass and mids sit within 0.3 dB of target, so voices sound natural. 108 dB/mW sensitivity runs easily from a phone.

Cons: Upper bass is about 2.3 dB high, and peaks of about 7 dB near 8.2 and 10.6 kHz make the treble bright and sharp. The Truthear x Crinacle Zero RED rates much higher for less.

Is the CVJ Mermaid II right for you?

Buy it if

  • you want the tuning most listeners prefer in blind tests out of the box (Harman score 77).
  • you want sub-bass rumble that reaches down to 20 Hz.

Skip it if

BackClosed
Built-in MicrophoneNo
ConnectionWired
Deviation From Target1.93 dB standard deviation
Driver TypeDynamic
Drivers1 x 10mm dynamic
Form FactorIn-ear
Harman Preference Score77 (average of 2 squig.link measurements scored separately, calibrated to AutoEQ)
Impedance22 ohms
Sensitivity108 dB/mW
Sub-bass ExtensionWithin 6 dB of target down to 20 Hz (-2.5 dB at 30 Hz)
Tonal Tilt+0.19 (negative is warmer, positive brighter)

EQ Presets

Harman target

Set a preamp of -3.4 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Harman match with this EQ: 91 out of 100, up from 77.

FilterFrequencyGainQ
Low shelf105 Hz+1.5 dB0.70
High shelf10,000 Hz-4.0 dB0.70
Peak24 Hz+1.2 dB1.43
Peak164 Hz-3.1 dB0.75
Peak733 Hz+1.0 dB2.82
Peak3,166 Hz+1.8 dB3.64
Peak5,854 Hz+4.1 dB5.33
Peak8,000 Hz-3.0 dB6.00

Neutral target

Set a preamp of -3.4 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Neutral match with this EQ: 93 out of 100, up from 53.

FilterFrequencyGainQ
Low shelf105 Hz-7.0 dB0.70
High shelf10,000 Hz-4.0 dB0.70
Peak24 Hz+0.8 dB1.92
Peak154 Hz-3.1 dB0.66
Peak723 Hz+1.0 dB2.59
Peak1,533 Hz-0.6 dB2.61
Peak3,165 Hz+1.8 dB3.60
Peak5,854 Hz+4.1 dB5.32
Peak8,000 Hz-3.0 dB6.00

Studio flat target

Set a preamp of -4.0 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Studio flat match with this EQ: 93 out of 100, up from 35.

FilterFrequencyGainQ
Low shelf105 Hz-9.6 dB0.70
High shelf10,000 Hz+1.6 dB0.70
Peak170 Hz-5.0 dB0.73
Peak744 Hz+0.9 dB2.94
Peak2,836 Hz+4.0 dB2.52
Peak4,516 Hz-1.7 dB6.00
Peak6,072 Hz+1.8 dB6.00
Peak7,903 Hz-2.7 dB6.00

Warm target

Set a preamp of -3.0 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Warm match with this EQ: 91 out of 100, up from 72.

FilterFrequencyGainQ
Low shelf105 Hz+1.7 dB0.70
High shelf10,000 Hz-6.0 dB0.70
Peak24 Hz+1.3 dB1.43
Peak160 Hz-2.9 dB0.79
Peak732 Hz+1.2 dB2.71
Peak1,758 Hz-1.1 dB2.20
Peak4,388 Hz-1.9 dB4.61
Peak6,014 Hz+1.6 dB6.00
Peak8,000 Hz-5.5 dB5.19

Bass target

Set a preamp of -6.3 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Bass match with this EQ: 92 out of 100, up from 63.

FilterFrequencyGainQ
Low shelf105 Hz+5.1 dB0.70
High shelf10,000 Hz-4.0 dB0.70
Peak30 Hz+1.3 dB1.40
Peak85 Hz-0.6 dB2.35
Peak174 Hz-3.1 dB0.83
Peak736 Hz+1.0 dB2.91
Peak1,530 Hz-0.6 dB2.61
Peak3,167 Hz+1.8 dB3.66
Peak5,854 Hz+4.1 dB5.34
Peak8,000 Hz-3.0 dB6.00

Bright target

Set a preamp of -4.8 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 89 out of 100, up from 44.

FilterFrequencyGainQ
Low shelf105 Hz-7.1 dB0.70
Peak154 Hz-3.2 dB0.65
Peak3,126 Hz+1.7 dB5.05
Peak5,345 Hz+4.7 dB1.49

V-shaped target

Set a preamp of -5.6 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted V-shaped match with this EQ: 86 out of 100, up from 66.

FilterFrequencyGainQ
Low shelf105 Hz+5.5 dB0.70
High shelf10,000 Hz+1.3 dB0.70
Peak5,020 Hz+4.5 dB1.09

Frequency Response

How the CVJ Mermaid II measures across the audible range, against the Harman in-ear target that most listeners prefer in blind tests. Where the line sits above the target that range sounds louder (more bass, brighter treble), below it quieter. The curve is the average of 2 independent measurements, and both lines are shifted so their 500 Hz to 2 kHz average sits at 0 dB.

CVJ Mermaid IIHarman target
Measured frequency response of the CVJ Mermaid II-24-18-12-60+6+12+18dB20501002005001k2k5k10k20k

Measurement data: the average of 2 independent measurements from the squig.link databases of soundignity and tonedeafmonk. Thanks to each of them for publishing their work.

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