As someone who is following this technology while not really an expert (I'm a computational biologist in my day job) LoRA is a way of reducing the number of parameters in a large language model (LLM, the technology behind all these new chatbots) so that it can be run on less powerful hardware (say a laptop or even a phone). The OP is saying that the improvements this chatbot provides isn't so much being more clever about reducing parameters but being trained on text that has been cleaned up rather than the rather messy training sets used in other small LLMs.
LoRA (Low-Rank Adapter) is way to customize/finetune the LLM to a new datasets without needing to retrain the entire network (which makes it better (and in theory easier to do). It doesn't not change the speed significantly afaik
