Most model releases ask you to judge one endpoint. This one exposes a 2×3 map: tiny and flash, each with pre-trained, mid-trained, and WSM-merged checkpoints. That is the part of the Ling-3.0 base model release I find genuinely useful. All six are base checkpoints, not post-trained chat or instruct models, so the value is not “download a finished assistant.” It is being able to choose where to continue training or compare how the family changes from one stage to the next. No benchmark comparison was run for this post, and the WSM paper’s empirical setup was Ling-mini rather than these six checkpoints. The practical next step is to open the matching tiny and flash model cards side by side, pick one stage, and decide what would make a fair comparison. Which stage would you start from, and what would you measure across all three? submitted by /u/Asleep-Pilot-4142
Originally posted by u/Asleep-Pilot-4142 on r/ArtificialInteligence