TRN MT4 Pro Review: Ranked #610 of 1253

Last updated: October 16, 2026

The TRN MT4 Pro ranks #610 out of 1253 total In-Ear Headphones for sound quality. See all Headphones rankings for every top pick.

Brand: TRN

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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#610 TRN MT4 Pro: $16.99 Amazon $16.99 eBay

Older model: the TRN MT4 (ranked lower, rated 3.6/5). See every TRN MT1 generation.

Same family: the TRN MT1 Pro (lower-end model, ranked higher, rated 4.1/5), the TRN MT3 (lower-end model, ranked higher, rated 4.8/5) and the TRN MT5 (higher-end model, ranked higher, rated 4.3/5).

Pros: A broadly balanced tuning with a preference score of 71 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 TRN MT4 Pro right for you?

Buy it if

  • your taste runs warm: it scores 83 for that sound.
  • you are sensitive to bright or sharp treble (treble sits 4.4 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 13 points.

Skip it if

  • you want the best value: the higher-rated CCA Polaris costs about $4 less.
BackClosed
ConnectionWired
Deviation From Target2.05 dB standard deviation
Driver TypeDual Dynamic
Drivers1 x 10mm dynamic + 1 x 6mm dynamic
Form FactorIn-ear
Harman Preference Score71 (median of 5 squig.link measurements, calibrated to AutoEQ)
Sub-bass ExtensionWithin 6 dB of target down to 20 Hz (+0.3 dB at 30 Hz)
Tonal Tilt-0.64 (negative is warmer, positive brighter)

EQ Presets

Harman target

Set a preamp of -4.9 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the median of 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Harman match with this EQ: 84 out of 100, up from 71.

FilterFrequencyGainQ
Low shelf105 Hz+0.6 dB0.70
High shelf10,000 Hz-0.9 dB0.70
Peak654 Hz+1.3 dB2.15
Peak1,723 Hz-2.5 dB2.73
Peak3,068 Hz+3.4 dB6.00
Peak5,345 Hz+4.7 dB0.96
Peak6,873 Hz-1.6 dB6.00

Neutral target

Set a preamp of -4.9 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the median of 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Neutral match with this EQ: 85 out of 100, up from 36.

FilterFrequencyGainQ
Low shelf105 Hz-7.9 dB0.70
High shelf10,000 Hz-0.9 dB0.70
Peak1,723 Hz-2.5 dB2.73
Peak3,068 Hz+3.4 dB6.00
Peak5,345 Hz+4.7 dB0.96

Studio flat 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 Studio flat match with this EQ: 83 out of 100, up from 17.

FilterFrequencyGainQ
Low shelf105 Hz-10.5 dB0.70
High shelf10,000 Hz+2.0 dB0.70
Peak23 Hz-1.7 dB2.04
Peak66 Hz+1.0 dB4.20
Peak175 Hz-2.8 dB1.00
Peak1,673 Hz-2.2 dB3.02
Peak2,632 Hz+1.4 dB6.00
Peak3,148 Hz+6.0 dB1.73
Peak4,121 Hz-1.4 dB6.00
Peak5,712 Hz+4.4 dB5.16

Warm 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 median of 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Warm match with this EQ: 90 out of 100, up from 83.

FilterFrequencyGainQ
Low shelf105 Hz+0.8 dB0.70
High shelf10,000 Hz-4.2 dB0.70
Peak649 Hz+1.6 dB1.71
Peak1,767 Hz-2.8 dB2.89
Peak3,083 Hz+3.1 dB6.00
Peak4,361 Hz-1.6 dB6.00
Peak5,751 Hz+3.5 dB1.28

Bass target

Set a preamp of -4.9 dB, then add these filters in any parametric equalizer (Wavelet, Equalizer APO, Peace, or a player with parametric EQ). Calculated by Speaker Ranking from the median of 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bass match with this EQ: 86 out of 100, up from 73.

FilterFrequencyGainQ
Low shelf105 Hz+4.4 dB0.70
High shelf10,000 Hz-0.9 dB0.70
Peak653 Hz+1.3 dB2.14
Peak1,723 Hz-2.5 dB2.72
Peak3,068 Hz+3.4 dB6.00
Peak5,345 Hz+4.7 dB0.96
Peak6,873 Hz-1.6 dB6.00

Bright 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 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 73 out of 100, up from 23.

FilterFrequencyGainQ
Low shelf105 Hz-8.0 dB0.70
High shelf10,000 Hz+1.6 dB0.70
Peak1,782 Hz-3.1 dB2.28
Peak3,573 Hz+6.0 dB1.27
Peak5,586 Hz+4.2 dB4.76

V-shaped 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 5 squig.link measurements, in the filter layout AutoEQ uses. Predicted V-shaped match with this EQ: 72 out of 100, up from 61.

FilterFrequencyGainQ
Low shelf105 Hz+5.0 dB0.70
High shelf10,000 Hz+2.0 dB0.70
Peak424 Hz+1.3 dB0.84
Peak1,742 Hz-3.1 dB2.11
Peak3,354 Hz+6.0 dB1.23
Peak5,487 Hz+4.4 dB3.91

Frequency Response

How the TRN MT4 Pro 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.

TRN MT4 ProHarman target
Measured frequency response of the TRN MT4 Pro-24-18-12-60+6+12+18dB20501002005001k2k5k10k20k

Measurement data: median of 5 measurements from the squig.link databases of ankramutt, eplv, pw, scboy and soundcheck39. Thanks to each of them for publishing their work.

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