Big Podcasts, Small Podcasts: Analysis Finds They Sound The Same.

The biggest podcasts may have millions of listeners, professional production teams and expensive recording equipment, but when it comes to sound quality, they have little advantage over smaller independent shows. A new analysis from Diffio AI finds that podcasts appearing on Apple’s U.S. charts sound virtually identical to those outside the rankings, raising questions about how much production resources really matter when it comes to delivering clear audio.

The findings come from an analysis of 3,525 episodes across 1,438 English-language podcasts, including shows appearing on Apple’s top 100 charts across 18 genres and active podcasts outside those rankings. Using an automated speech-quality model that scores recordings on a five-point scale, Diffio AI found both charting and non-charting podcasts earned an identical median score of 4.06.

Even among charting podcasts, popularity offered little advantage. Shows ranked in the top 10 of their respective genres earned a median score of 4.09 vs. 4.05 for those ranked between 51 and 100.

There was, however, one notable difference. Top-ranked podcasts were less likely to have episodes with weaker sound quality. About 13% of episodes from top 10 shows scored below 3.5 vs. 20% among those ranked 51 through 100. The findings suggest that while larger podcasts may be more consistent in their production, smaller shows are capable of delivering comparable sound quality.

Diffio AI, which develops speech enhancement software, acknowledges its commercial interest in audio quality research. The company says its tools were not used to modify any of the podcast recordings analyzed.

Technology Advances, Little Improvement

Perhaps more surprising is how little podcast audio quality has changed despite nearly a decade of technological innovation. Diffio AI examined historical episodes from 476 charting podcasts dating back to 2017, a period that saw major advances in microphones, remote recording platforms, editing software and, more recently, artificial intelligence tools designed to improve speech quality.

Yet average scores increased only modestly, from 3.85 in 2017 to 4.00 in 2026.

The review found little evidence that the pandemic-era shift to remote recording significantly affected podcast sound quality. Between 2019 and 2020, scores among the same shows increased by just 0.05 points, a difference that was not statistically significant.

Diffio AI also found that higher audio bitrates did not translate into better results. Episodes encoded at 64 kbps or less earned a median score of 4.06, virtually identical to the 4.07 recorded by episodes exceeding 200 kbps.

Genre Matters More

While popularity made little difference, podcast genre produced considerably wider variations.

Technology podcasts led the rankings with a median audio quality score of 4.27, followed by Health & Fitness at 4.24, News at 4.23 and Business at 4.21.

At the other end were Kids & Family podcasts, which scored 3.54, and Fiction podcasts at 3.68. Comedy and Sports each earned 3.89.

But those differences don’t necessarily mean some genres are less professionally produced. Diffio AI cautions that its measurement system evaluates speech quality, meaning background music, sound effects and other production elements can lower scores even when they are intentionally included. That makes the results particularly relevant for genres dominated by spoken-word programming, where clear dialogue is the primary focus.

What The Findings Mean

The analysis offers an encouraging message for independent creators competing against larger podcast networks as expensive production resources aren’t necessarily required to deliver professional-sounding audio. But it also suggests that technology alone may not be enough to improve the listening experience. Despite years of investment in recording equipment and production tools, the industry’s overall speech-quality scores have remained relatively stable.

There are limitations to the findings. The analysis relied on SCOREQ, an automated model that predicts perceived speech quality, rather than a panel of human listeners. Diffio AI also analyzed only three 24-second samples from each episode, meaning individual scores may not reflect an entire program. And while the study measured technical sound quality, it didn’t examine whether listeners notice those differences or whether they influence audience growth, engagement or retention.