Sphinx speech recognition
Ricky Houghton first brought us the Sphinx benchmark through his association with speech recognition efforts at Carnegie Mellon University. Sphinx is a high-quality speech recognition routine that needs the latest computer hardware to run at speeds close to real-time processing. We use two different versions, built with two different compilers, in an attempt to ensure we're getting the best possible performance.

There are two goals with Sphinx. The first is to run it faster than real time, so real-time speech recognition is possible. The second, more ambitious goal is to run it at about 0.8 times real time, where additional CPU overhead is available for other sorts of processing, enabling Sphinx-driven real-time applications.

Sphinx loves memory bandwidth, so the 3500+ does well. The chip can't quite catch Intel's fastest Prescotts, but it's close.

LAME MP3 encoding
We used LAME to encode a 101MB 16-bit, 44KHz audio file into a very high-quality MP3. The exact command-line options we used were:

lame --alt-preset extreme file.wav file.mp3

DivX video encoding
This new version of XMPEG includes a benchmark feature, so we're reporting scores in frames per second now.

If the 3500+ has a weakness, it's media encoding. The chip can only manage a middle-of-the-pack performance with LAME MP3 encoding, and there's no touching Intel's Pentium 4s when it comes to DivX video encoding.