Acoustune HS1657CU Review: Ranked #289 of 1476

Last updated: October 21, 2026

The Acoustune HS1657CU ranks #289 out of 1476 total In-Ear Headphones for sound quality. See all Headphones rankings for every top pick.

Brand: Acoustune

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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Acoustune HS1657CU - ranked #289 of 1476 In-Ear Headphones · Editor's rating 4.3/5

#289 Acoustune HS1657CU: $480 eBay

Pros: A single dynamic IEM in a brass acoustic chamber with a preference score of 77. Bass and midrange stay within about 2 dB of target down to 20 Hz, so it sounds full and natural, and the Pentaconn Ear cable is detachable.

Cons: A 6.3 dB peak near 8.9 kHz beside a 4.7 dB dip near 3.6 kHz makes the treble uneven, so some cymbals stand out while vocal edges recede. It was sold mainly in Japan at about $480, Acoustune does not publish impedance or sensitivity, and the score rests on a single measurement.

Is the Acoustune HS1657CU 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

ReleasedJul 2020 (6 years ago)
BackClosed
ConnectionWired
Deviation From Target1.93 dB standard deviation
Driver TypeDynamic
Drivers1 x dynamic (4th gen Myrinx)
Form FactorIn-ear
Harman Preference Score77 (1 squig.link measurement, calibrated to AutoEQ)
Sub-bass ExtensionWithin 6 dB of target down to 20 Hz (-1.1 dB at 30 Hz)
Tonal Tilt-0.03 (negative is warmer, positive brighter)

EQ Presets

Harman target

Set a preamp of -5.9 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from a single measurement from squig.link, in the filter layout AutoEQ uses. Predicted Harman match with this EQ: 90 out of 100, up from 77.

FilterFrequencyGainQ
Low shelf105 Hz+1.1 dB0.70
High shelf10,000 Hz-4.6 dB0.70
Peak139 Hz-2.9 dB1.16
Peak435 Hz+1.8 dB2.57
Peak2,132 Hz-2.3 dB4.06
Peak3,074 Hz+1.4 dB6.00
Peak3,654 Hz+5.8 dB3.50
Peak5,473 Hz-3.1 dB6.00
Peak7,121 Hz+2.0 dB3.48

Neutral target

Set a preamp of -5.9 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from a single measurement from squig.link, in the filter layout AutoEQ uses. Predicted Neutral match with this EQ: 92 out of 100, up from 45.

FilterFrequencyGainQ
Low shelf105 Hz-7.4 dB0.70
High shelf10,000 Hz-4.6 dB0.70
Peak128 Hz-3.0 dB0.98
Peak217 Hz-1.0 dB3.46
Peak434 Hz+1.8 dB2.51
Peak2,134 Hz-2.3 dB4.09
Peak3,074 Hz+1.4 dB6.00
Peak3,654 Hz+5.8 dB3.49
Peak5,473 Hz-3.1 dB6.00
Peak7,122 Hz+2.0 dB3.48

Studio flat 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 a single measurement from squig.link, in the filter layout AutoEQ uses. Predicted Studio flat match with this EQ: 92 out of 100, up from 28.

FilterFrequencyGainQ
Low shelf105 Hz-10.0 dB0.70
High shelf10,000 Hz+1.6 dB0.70
Peak151 Hz-4.8 dB1.00
Peak441 Hz+1.2 dB3.05
Peak2,000 Hz-1.1 dB5.84
Peak3,325 Hz+6.0 dB2.94
Peak4,039 Hz+2.2 dB4.89
Peak5,498 Hz-5.5 dB6.00
Peak7,106 Hz+2.0 dB5.97

Warm target

Set a preamp of -4.1 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from a single measurement from squig.link, in the filter layout AutoEQ uses. Predicted Warm match with this EQ: 89 out of 100, up from 73.

FilterFrequencyGainQ
Low shelf105 Hz+1.4 dB0.70
High shelf10,000 Hz-6.0 dB0.70
Peak133 Hz-2.7 dB1.21
Peak445 Hz+1.9 dB2.16
Peak2,138 Hz-3.0 dB3.37
Peak3,135 Hz+1.4 dB6.00
Peak3,683 Hz+4.2 dB4.25
Peak5,544 Hz-5.2 dB6.00

Bass target

Set a preamp of -5.9 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from a single measurement from squig.link, in the filter layout AutoEQ uses. Predicted Bass match with this EQ: 91 out of 100, up from 66.

FilterFrequencyGainQ
Low shelf105 Hz+4.9 dB0.70
High shelf10,000 Hz-4.6 dB0.70
Peak30 Hz+1.0 dB1.38
Peak143 Hz-2.9 dB1.24
Peak435 Hz+1.8 dB2.59
Peak2,132 Hz-2.3 dB4.05
Peak3,074 Hz+1.4 dB6.00
Peak3,654 Hz+5.8 dB3.50
Peak5,473 Hz-3.1 dB6.00
Peak7,121 Hz+2.0 dB3.48

Bright 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 a single measurement from squig.link, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 81 out of 100, up from 36.

FilterFrequencyGainQ
Low shelf105 Hz-7.4 dB0.70
High shelf10,000 Hz-1.0 dB0.70
Peak128 Hz-3.0 dB0.96
Peak2,123 Hz-2.5 dB4.04
Peak3,848 Hz+6.0 dB2.09

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 a single measurement from squig.link, in the filter layout AutoEQ uses. Predicted V-shaped match with this EQ: 79 out of 100, up from 67.

FilterFrequencyGainQ
Low shelf105 Hz+5.5 dB0.70
Peak417 Hz+2.4 dB2.96
Peak2,081 Hz-2.0 dB2.62
Peak3,208 Hz+1.7 dB6.00
Peak3,893 Hz+6.0 dB1.78

Frequency Response

How the Acoustune HS1657CU 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 a single measurement, and both lines are shifted so their 500 Hz to 2 kHz average sits at 0 dB.

Acoustune HS1657CUHarman target
Measured frequency response of the Acoustune HS1657CU-24-18-12-60+6+12+18dB20501002005001k2k5k10k20k

Measurement data: a single measurement from the squig.link database of kazi. Thanks to them for publishing their work.

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