The Tangzu Nezha ranks #884 out of 1291 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 16, 2026 at 5:46 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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#884 Tangzu Nezha: $399.00 Linsoul $399.00 eBay
Pros: A broadly balanced tuning with a preference score of 66 against the Harman target.
Cons: Treble about 3 dB below target from 3 to 10 kHz, which can sound dull or veiled next to brighter headphones. An uneven response, 2.6 dB standard deviation from target.
Is the Tangzu Nezha right for you?
Buy it if
- you are sensitive to bright or sharp treble (treble sits 2.7 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 22 points.
Skip it if
- you want the best value: the higher-rated EPZ G10 costs about $375 less.
| Back | Closed |
|---|---|
| Connection | Wired |
| Deviation From Target | 2.61 dB standard deviation |
| Driver Type | Hybrid (6 BA + 1 PZT) |
| Drivers | 6 x balanced armature (2 Sonion subwoofers + 4 custom BA) + 1 x piezoelectric (PZT) driver |
| Form Factor | In-ear |
| Frequency Response | 10Hz - 20kHz |
| Harman Preference Score | 66 (median of 5 squig.link measurements, calibrated to AutoEQ) |
| Impedance | 16 ohms |
| Sensitivity | 106 dB |
| Sub-bass Extension | Within 6 dB of target down to 20 Hz (-4.4 dB at 30 Hz) |
| Tonal Tilt | -0.27 (negative is warmer, positive brighter) |
EQ Presets
Harman target
Set a preamp of -4.7 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 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Harman match with this EQ: 88 out of 100, up from 66.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | +2.3 dB | 0.70 |
| High shelf | 10,000 Hz | -3.7 dB | 0.70 |
| Peak | 182 Hz | -3.9 dB | 0.58 |
| Peak | 4,109 Hz | +4.7 dB | 0.89 |
Neutral target
Set a preamp of -4.7 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 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Neutral match with this EQ: 91 out of 100, up from 43.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | -6.3 dB | 0.70 |
| High shelf | 10,000 Hz | -3.7 dB | 0.70 |
| Peak | 174 Hz | -4.0 dB | 0.54 |
| Peak | 4,109 Hz | +4.7 dB | 0.89 |
Studio flat target
Set a preamp of -6.0 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 median of 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Studio flat match with this EQ: 93 out of 100, up from 23.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | -8.8 dB | 0.70 |
| High shelf | 10,000 Hz | +1.3 dB | 0.70 |
| Peak | 23 Hz | +0.9 dB | 1.35 |
| Peak | 185 Hz | -5.7 dB | 0.57 |
| Peak | 2,773 Hz | +5.9 dB | 1.23 |
| Peak | 4,331 Hz | +2.8 dB | 6.00 |
| Peak | 6,734 Hz | +1.3 dB | 4.37 |
Warm target
Set a preamp of -2.8 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 median of 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Warm match with this EQ: 89 out of 100, up from 72.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | +2.5 dB | 0.70 |
| High shelf | 10,000 Hz | -6.0 dB | 0.70 |
| Peak | 175 Hz | -3.7 dB | 0.62 |
| Peak | 3,893 Hz | +2.8 dB | 1.05 |
Bass target
Set a preamp of -5.4 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 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bass match with this EQ: 87 out of 100, up from 58.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | +5.4 dB | 0.70 |
| High shelf | 10,000 Hz | -3.7 dB | 0.70 |
| Peak | 199 Hz | -3.8 dB | 0.64 |
| Peak | 4,109 Hz | +4.7 dB | 0.89 |
Bright target
Set a preamp of -6.1 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 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 87 out of 100, up from 30.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | -6.3 dB | 0.70 |
| Peak | 174 Hz | -4.0 dB | 0.53 |
| Peak | 4,235 Hz | +6.0 dB | 0.92 |
V-shaped target
Set a preamp of -6.2 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 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted V-shaped match with this EQ: 85 out of 100, up from 57.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | +5.6 dB | 0.70 |
| High shelf | 10,000 Hz | +1.1 dB | 0.70 |
| Peak | 46 Hz | +1.0 dB | 1.80 |
| Peak | 214 Hz | -2.3 dB | 0.58 |
| Peak | 1,161 Hz | -1.2 dB | 2.79 |
| Peak | 2,207 Hz | +1.5 dB | 4.65 |
| Peak | 4,082 Hz | +6.0 dB | 0.86 |
| Peak | 5,665 Hz | +1.5 dB | 6.00 |
- Reviews, Comparisons and Sound Samples
Frequency Response
How the Tangzu Nezha 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 5 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.
Measurement data: median of 5 measurements from the squig.link databases of hu-fi, lown-fi, sl0the, therollo9 and timmyv. Thanks to each of them for publishing their work.
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