The Sonic Memory SM1 ranks #307 out of 1253 total In-Ear Headphones for sound quality. See all Headphones rankings for every top pick.
Brand: Sonic Memory
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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#307 Sonic Memory SM1: $59 Discontinued eBay
Pros: A broadly balanced tuning with a preference score of 76 against the Harman target.
Cons: The rating reflects sound quality only; comfort, build and noise isolation are not part of the score. Discontinued.
Is the Sonic Memory SM1 right for you?
Buy it if
- you want the tuning most listeners prefer in blind tests out of the box (Harman score 76).
- your taste runs warm: it scores 85 for that sound.
- you want sub-bass rumble that reaches down to 20 Hz.
Skip it if
- you want to buy it new: it is discontinued.
| Back | Closed |
|---|---|
| Connection | Wired |
| Deviation From Target | 1.64 dB standard deviation |
| Driver Type | Dynamic |
| Drivers | 1 x dynamic |
| Form Factor | In-ear |
| Harman Preference Score | 76 (median of 3 squig.link measurements, calibrated to AutoEQ) |
| Sub-bass Extension | Within 6 dB of target down to 20 Hz (-0.5 dB at 30 Hz) |
| Tonal Tilt | -0.48 (negative is warmer, positive brighter) |
EQ Presets
Harman target
Set a preamp of -3.7 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 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Harman match with this EQ: 90 out of 100, up from 76.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | -0.3 dB | 0.70 |
| High shelf | 10,000 Hz | -5.9 dB | 0.70 |
| Peak | 186 Hz | -2.8 dB | 0.72 |
| Peak | 2,597 Hz | +2.9 dB | 3.13 |
| Peak | 4,245 Hz | -1.6 dB | 5.05 |
| Peak | 5,979 Hz | +4.1 dB | 2.39 |
Neutral target
Set a preamp of -3.7 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 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Neutral match with this EQ: 91 out of 100, up from 40.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | -8.9 dB | 0.70 |
| High shelf | 10,000 Hz | -5.9 dB | 0.70 |
| Peak | 186 Hz | -2.7 dB | 0.61 |
| Peak | 2,597 Hz | +2.9 dB | 3.12 |
| Peak | 4,247 Hz | -1.6 dB | 5.10 |
| Peak | 5,979 Hz | +4.1 dB | 2.39 |
Studio flat 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 median of 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Studio flat match with this EQ: 91 out of 100, up from 20.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | -11.5 dB | 0.70 |
| High shelf | 10,000 Hz | -0.4 dB | 0.70 |
| Peak | 184 Hz | -4.5 dB | 0.67 |
| Peak | 2,621 Hz | +5.7 dB | 2.48 |
| Peak | 4,261 Hz | -2.1 dB | 5.57 |
| Peak | 6,170 Hz | +2.8 dB | 4.70 |
Warm target
Set a preamp of -1.8 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 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Warm match with this EQ: 92 out of 100, up from 85.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| High shelf | 10,000 Hz | -6.0 dB | 0.70 |
| Peak | 186 Hz | -2.6 dB | 0.76 |
| Peak | 2,599 Hz | +1.8 dB | 3.44 |
| Peak | 4,193 Hz | -2.5 dB | 5.42 |
| Peak | 6,007 Hz | +2.3 dB | 6.00 |
Bass target
Set a preamp of -3.7 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 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bass match with this EQ: 92 out of 100, up from 75.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | +3.4 dB | 0.70 |
| High shelf | 10,000 Hz | -5.9 dB | 0.70 |
| Peak | 191 Hz | -2.8 dB | 0.79 |
| Peak | 2,598 Hz | +2.9 dB | 3.13 |
| Peak | 4,244 Hz | -1.6 dB | 5.04 |
| Peak | 5,979 Hz | +4.1 dB | 2.40 |
Bright target
Set a preamp of -3.9 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 3 squig.link measurements, in the filter layout AutoEQ uses. Predicted Bright match with this EQ: 86 out of 100, up from 29.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | -8.9 dB | 0.70 |
| High shelf | 10,000 Hz | -3.0 dB | 0.70 |
| Peak | 186 Hz | -2.7 dB | 0.57 |
| Peak | 2,599 Hz | +1.8 dB | 4.51 |
| Peak | 3,985 Hz | -2.1 dB | 6.00 |
| Peak | 5,345 Hz | +4.1 dB | 0.70 |
V-shaped target
Set a preamp of -4.2 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: 82 out of 100, up from 69.
| Filter | Frequency | Gain | Q |
|---|---|---|---|
| Low shelf | 105 Hz | +4.1 dB | 0.70 |
| High shelf | 10,000 Hz | -1.9 dB | 0.70 |
| Peak | 2,632 Hz | +2.0 dB | 4.71 |
| Peak | 3,962 Hz | -1.9 dB | 6.00 |
| Peak | 5,345 Hz | +4.2 dB | 0.59 |
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Frequency Response
How the Sonic Memory SM1 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.
Measurement data: median of 3 measurements from the squig.link databases of aquaphobic, hu-fi and therollo9. Thanks to each of them for publishing their work.