SymphonyEars Hexad II Review: Ranked #840 of 1253

Last updated: October 16, 2026

The SymphonyEars Hexad II ranks #840 out of 1253 total In-Ear Headphones for sound quality. See all Headphones rankings for every top pick.

Brand: SymphonyEars

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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SymphonyEars Hexad II - ranked #840 of 1253 In-Ear Headphones · Editor's rating 3.5/5

#840 SymphonyEars Hexad II: $499 eBay

Older model: the SymphonyEars Hexad (ranked higher, rated 4/5). See every SymphonyEars Hexad generation.

Pros: A broadly balanced tuning with a preference score of 67 against the Harman target.

Cons: Treble about 4 dB below target from 3 to 10 kHz, which can sound dull or veiled next to brighter headphones. An uneven response, 2.0 dB standard deviation from target.

Is the SymphonyEars Hexad II right for you?

Buy it if

  • your taste runs warm: it scores 80 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 20 points.

Skip it if

  • you want the best value: the higher-rated EPZ G10 costs about $475 less.
BackClosed
ConnectionWired (3.5mm / 4.4mm)
Deviation From Target2.01 dB standard deviation
Driver TypeBalanced Armature
Drivers6 Balanced Armature
Form FactorIn-ear
Harman Preference Score67 (median of 3 squig.link measurements, calibrated to AutoEQ)
Sub-bass ExtensionWithin 6 dB of target down to 20 Hz (-1.4 dB at 30 Hz)
Tonal Tilt-0.69 (negative is warmer, positive brighter)

EQ Presets

Harman target

Set a preamp of -4.4 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 Harman match with this EQ: 87 out of 100, up from 67.

FilterFrequencyGainQ
Low shelf105 Hz+0.5 dB0.70
High shelf10,000 Hz-4.6 dB0.70
Peak23 Hz-0.8 dB2.49
Peak81 Hz+0.7 dB1.28
Peak544 Hz-2.0 dB1.06
Peak2,088 Hz+2.0 dB3.05
Peak4,419 Hz+4.4 dB0.56
Peak6,334 Hz-1.2 dB5.50

Neutral target

Set a preamp of -4.4 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 Neutral match with this EQ: 88 out of 100, up from 36.

FilterFrequencyGainQ
Low shelf105 Hz-8.0 dB0.70
High shelf10,000 Hz-4.6 dB0.70
Peak540 Hz-2.0 dB1.02
Peak2,087 Hz+2.0 dB3.04
Peak4,419 Hz+4.4 dB0.56

Studio flat target

Set a preamp of -6.5 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 Studio flat match with this EQ: 85 out of 100, up from 16.

FilterFrequencyGainQ
Low shelf105 Hz-10.6 dB0.70
High shelf10,000 Hz+0.7 dB0.70
Peak24 Hz-1.6 dB1.79
Peak68 Hz+0.9 dB2.92
Peak166 Hz-0.7 dB2.45
Peak398 Hz-2.6 dB0.51
Peak2,603 Hz+6.0 dB1.13
Peak5,568 Hz+1.1 dB0.48

Warm target

Set a preamp of -3.3 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 Warm match with this EQ: 93 out of 100, up from 80.

FilterFrequencyGainQ
Low shelf105 Hz+0.8 dB0.70
High shelf10,000 Hz-6.0 dB0.70
Peak595 Hz-1.6 dB0.89
Peak2,443 Hz+3.2 dB0.96
Peak7,886 Hz+2.0 dB1.21

Bass target

Set a preamp of -4.4 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 Bass match with this EQ: 89 out of 100, up from 68.

FilterFrequencyGainQ
Low shelf105 Hz+4.3 dB0.70
High shelf10,000 Hz-4.6 dB0.70
Peak546 Hz-2.0 dB1.07
Peak2,088 Hz+2.0 dB3.06
Peak4,419 Hz+4.4 dB0.56

Bright 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 82 out of 100, up from 23.

FilterFrequencyGainQ
Low shelf105 Hz-8.0 dB0.70
High shelf10,000 Hz-1.5 dB0.70
Peak23 Hz-1.3 dB1.71
Peak546 Hz-2.1 dB1.00
Peak1,092 Hz-0.9 dB2.83
Peak2,441 Hz+1.5 dB1.34
Peak5,345 Hz+5.5 dB0.47
Peak7,022 Hz-3.6 dB5.52

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 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted V-shaped match with this EQ: 77 out of 100, up from 55.

FilterFrequencyGainQ
Low shelf105 Hz+5.0 dB0.70
High shelf10,000 Hz-0.4 dB0.70
Peak135 Hz+1.5 dB0.86
Peak781 Hz-2.2 dB1.32
Peak2,443 Hz+1.9 dB2.24
Peak3,807 Hz+0.8 dB1.97
Peak5,345 Hz+5.6 dB0.43
Peak7,058 Hz-3.8 dB5.12

Frequency Response

How the SymphonyEars Hexad 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.

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

Measurement data: median of 3 measurements from the squig.link databases of audioamigo, jaytiss and superreview. Thanks to each of them for publishing their work.

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