llama.cpp officially upgraded to version 1.0.0

On November 13, 2026, at 10:39, the Juejin platform published an article titled "llama.cpp Complete Tutorial: The Impact of Storage Media on Large Model Loading Performance". The piece reports on hands-on tests that measure how long it takes to load the same 475.25 GiB set of model weights from three different storage media, with the goal of showing how hardware choices shape the efficiency of running large models locally.

In the measurements, each medium was read once with the same weights. Loading from onboard NVMe took 39.6 seconds, from a local disk it took 114 seconds, and from a NAS it took 4420 seconds, producing a gap of up to 112x between the fastest and the slowest option. The article frames this as a trade-off: money saved on the drive translates into waiting 73 extra minutes on each load, and it argues that the test data clearly demonstrates the decisive role storage hardware plays in the read performance of large models running on local machines.

As of now, this topic is covered only by this single report, so the discussion rests entirely on the measurements and conclusions presented in that article, with no follow-up results or independent verification available yet.