FiiO Snowsky Oak Nano Review: Ranked #439 of 1476

Last updated: October 21, 2026

The FiiO Snowsky Oak Nano ranks #439 out of 1476 total In-Ear Headphones for sound quality. See all Headphones rankings for every top pick.

Brand: Fiio

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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#439 FiiO Snowsky Oak Nano: $499.99 Amazon $499.99 eBay

Pros: A titanium shelled 13.8 mm beryllium alloy dynamic IEM at about $500 with a preference score of 75 across two measurements. The midrange stays within 1.5 dB of target, and the cable swaps between 3.5 mm, 4.4 mm and USB C plugs.

Cons: Sub bass is 4.4 dB below target, so the lowest notes are light. Treble is jagged, with a 6.8 dB dip near 6.3 kHz and peaks of 5.0 dB near 7.9 kHz and 5.6 dB near 11.2 kHz, which can add glare on some recordings.

Is the FiiO Snowsky Oak Nano right for you?

Buy it if

  • you want the tuning most listeners prefer in blind tests out of the box (Harman score 75).
  • you are sensitive to bright or sharp treble (treble sits 2.4 dB below target).

Skip it if

  • you want more bass (about 2 dB below target).
  • you want the best value: the higher-rated QCY HT05 MeloBuds ANC costs about $466 less.
Released2026 (this year)
BackClosed
ConnectionWired
Deviation From Target2.19 dB standard deviation
Driver TypeDynamic
Drivers1 x 13.8mm beryllium alloy dynamic
Form FactorIn-ear
Frequency Response10Hz - 40kHz (Manufacturer specified)
Harman Preference Score75 (average of 2 squig.link measurements scored separately, calibrated to AutoEQ)
Impedance50 ohms
Sensitivity112 dB/mW at 1 kHz
Sub-bass ExtensionWithin 6 dB of target down to 20 Hz (-4.3 dB at 30 Hz)
Tonal Tilt+0.22 (negative is warmer, positive brighter)

EQ Presets

Harman target

Set a preamp of -5.7 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 average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Harman match with this EQ: 90 out of 100, up from 75.

FilterFrequencyGainQ
Low shelf105 Hz+3.7 dB0.70
High shelf10,000 Hz+1.1 dB0.70
Peak23 Hz+1.6 dB1.40
Peak109 Hz-1.8 dB0.79
Peak232 Hz-0.9 dB2.53
Peak1,476 Hz-0.9 dB3.53
Peak3,157 Hz+2.9 dB3.33
Peak5,764 Hz+5.6 dB3.72

Neutral target

Set a preamp of -5.7 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 average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Neutral match with this EQ: 89 out of 100, up from 57.

FilterFrequencyGainQ
Low shelf105 Hz-4.9 dB0.70
High shelf10,000 Hz+1.1 dB0.70
Peak23 Hz+1.2 dB1.78
Peak109 Hz-1.9 dB0.70
Peak3,157 Hz+3.0 dB3.33
Peak5,764 Hz+5.6 dB3.71

Studio flat 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 average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Studio flat match with this EQ: 87 out of 100, up from 38.

FilterFrequencyGainQ
Low shelf105 Hz-7.5 dB0.70
High shelf10,000 Hz+2.0 dB0.70
Peak165 Hz-3.6 dB0.69
Peak2,841 Hz+3.2 dB4.08
Peak5,345 Hz+2.5 dB0.41
Peak6,887 Hz-0.7 dB0.40

Warm target

Set a preamp of -4.0 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 average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Warm match with this EQ: 87 out of 100, up from 73.

FilterFrequencyGainQ
Low shelf105 Hz+3.9 dB0.70
High shelf10,000 Hz-1.3 dB0.70
Peak5,931 Hz+4.3 dB6.00
Peak8,000 Hz-2.7 dB6.00

Bass target

Set a preamp of -6.3 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 average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Bass match with this EQ: 86 out of 100, up from 59.

FilterFrequencyGainQ
Low shelf105 Hz+5.8 dB0.70
High shelf10,000 Hz+1.1 dB0.70
Peak53 Hz+0.8 dB2.01
Peak198 Hz-1.6 dB1.38
Peak1,474 Hz-0.9 dB3.47
Peak3,158 Hz+2.9 dB3.33
Peak5,765 Hz+5.6 dB3.73

Bright target

Set a preamp of -4.8 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 average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 77 out of 100, up from 44.

FilterFrequencyGainQ
Low shelf105 Hz-4.9 dB0.70
High shelf10,000 Hz+2.0 dB0.70
Peak4,747 Hz+4.6 dB0.99

V-shaped 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 average of 2 independent measurements from squig.link, in the filter layout AutoEQ uses. Predicted V-shaped match with this EQ: 79 out of 100, up from 57.

FilterFrequencyGainQ
Low shelf105 Hz+6.0 dB0.70
High shelf10,000 Hz+2.0 dB0.70
Peak4,708 Hz+5.0 dB0.93

Frequency Response

How the FiiO Snowsky Oak Nano 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 average of 2 independent measurements, and both lines are shifted so their 500 Hz to 2 kHz average sits at 0 dB.

FiiO Snowsky Oak NanoHarman target
Measured frequency response of the FiiO Snowsky Oak Nano-24-18-12-60+6+12+18dB20501002005001k2k5k10k20k

Measurement data: the average of 2 independent measurements from the squig.link databases of atechreviews and audioamigo. Thanks to each of them for publishing their work.

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