TANGZU Wan'er S.G II Review: Ranked #453 of 1061

Last updated: October 15, 2026

The TANGZU Wan’er S.G II ranks #453 out of 1061 total In-Ear Headphones for sound quality. See all Headphones rankings for every top pick.

Brand: TANGZU

Prices on this page were last checked October 15, 2026 at 5:41 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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#453 TANGZU Wan’er S.G II: $24.00 Amazon $24.00 eBay

Pros: A very cheap single dynamic IEM, the second generation of the TANGZU Wan’er S.G. Measurements show bass right on the Harman target and full sub-bass to 20 Hz (score 72 across three measurements).

Cons: Treble sits about 4.0 dB below target, a dark, relaxed balance. Its score rests on three measurements.

Is the TANGZU Wan’er S.G II right for you?

Buy it if

  • your taste runs warm: it scores 81 for that sound.
  • you are sensitive to bright or sharp treble (treble sits 4.0 dB below target).
  • you want sub-bass rumble that reaches down to 20 Hz.
  • you are happy to use EQ: our preset lifts its Harman match by about 15 points.

Skip it if

  • you want the best value: the higher-rated TRN MT3 costs about $6 less.
Released2025 (1 year ago)
BackClosed
ConnectionWired
Deviation From Target2.07 dB standard deviation
Driver TypeDynamic
Drivers1 x 10mm dynamic
Form FactorIn-ear
Harman Preference Score72 (median of 3 squig.link measurements, calibrated to AutoEQ)
Impedance19 ohms
Sensitivity113.5 dB
Sub-bass ExtensionWithin 6 dB of target down to 20 Hz (-1.3 dB at 30 Hz)
Tonal Tilt-0.41 (negative is warmer, positive brighter)

EQ Presets

Harman target

Set a preamp of -5.3 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Harman match with this EQ: 87 out of 100, up from 72.

FilterFrequencyGainQ
Low shelf105 Hz+1.4 dB0.70
High shelf10,000 Hz-1.0 dB0.70
Peak164 Hz-1.7 dB0.93
Peak676 Hz+1.3 dB2.22
Peak1,939 Hz-2.3 dB2.79
Peak3,475 Hz+2.7 dB4.92
Peak5,345 Hz+5.2 dB1.34

Neutral target

Set a preamp of -5.3 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Neutral match with this EQ: 89 out of 100, up from 41.

FilterFrequencyGainQ
Low shelf105 Hz-7.2 dB0.70
High shelf10,000 Hz-1.0 dB0.70
Peak164 Hz-1.8 dB0.80
Peak661 Hz+1.3 dB2.02
Peak1,939 Hz-2.3 dB2.79
Peak3,475 Hz+2.7 dB4.92
Peak5,345 Hz+5.2 dB1.34

Studio flat target

Set a preamp of -5.2 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Studio flat match with this EQ: 86 out of 100, up from 23.

FilterFrequencyGainQ
Low shelf105 Hz-9.8 dB0.70
High shelf10,000 Hz+1.7 dB0.70
Peak172 Hz-3.6 dB0.81
Peak693 Hz+1.2 dB2.58
Peak1,820 Hz-1.8 dB2.74
Peak3,080 Hz+1.4 dB6.00
Peak3,807 Hz+4.9 dB1.29
Peak5,898 Hz+2.6 dB6.00

Warm target

Set a preamp of -3.5 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Warm match with this EQ: 90 out of 100, up from 81.

FilterFrequencyGainQ
Low shelf105 Hz+1.6 dB0.70
High shelf10,000 Hz-3.7 dB0.70
Peak164 Hz-1.5 dB1.06
Peak683 Hz+1.6 dB1.96
Peak1,978 Hz-2.8 dB2.69
Peak3,524 Hz+2.4 dB5.15
Peak5,479 Hz+3.6 dB1.83

Bass target

Set a preamp of -5.3 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bass match with this EQ: 89 out of 100, up from 68.

FilterFrequencyGainQ
Low shelf105 Hz+5.2 dB0.70
High shelf10,000 Hz-1.0 dB0.70
Peak168 Hz-1.7 dB1.03
Peak679 Hz+1.3 dB2.28
Peak1,939 Hz-2.3 dB2.79
Peak3,475 Hz+2.7 dB4.92
Peak5,345 Hz+5.2 dB1.34

Bright target

Set a preamp of -6.4 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 78 out of 100, up from 28.

FilterFrequencyGainQ
Low shelf105 Hz-7.2 dB0.70
High shelf10,000 Hz+1.1 dB0.70
Peak164 Hz-1.8 dB0.78
Peak663 Hz+1.3 dB1.98
Peak1,939 Hz-2.5 dB2.30
Peak3,394 Hz+1.8 dB5.50
Peak4,321 Hz+6.0 dB1.40
Peak5,741 Hz+2.8 dB6.00

V-shaped target

Set a preamp of -6.6 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted V-shaped match with this EQ: 75 out of 100, up from 61.

FilterFrequencyGainQ
Low shelf105 Hz+5.7 dB0.70
High shelf10,000 Hz+1.7 dB0.70
Peak558 Hz+1.2 dB1.91
Peak1,284 Hz-1.0 dB3.96
Peak1,939 Hz-2.3 dB2.03
Peak3,300 Hz+1.5 dB6.00
Peak4,056 Hz+6.0 dB1.34
Peak5,666 Hz+3.3 dB5.39

Frequency Response

How the TANGZU Wan’er S.G 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 median of 3 independent measurements, so one odd sample or rig cannot skew it, and both lines are shifted so their 500 Hz to 2 kHz average sits at 0 dB.

TANGZU Wan’er S.G IIHarman target
Measured frequency response of the TANGZU Wan’er S.G II-24-18-12-60+6+12+18dB20501002005001k2k5k10k20k

Measurement data: median of 3 measurements from the squig.link databases of lestat, pw and sl0the. Thanks to each of them for publishing their work.

Head-to-Head Comparisons

2 comparisons

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