Alpaca is an instruction-finetuned LLM based off of LLaMA.
The first of many instruct-finetuned versions of LLaMA, Alpaca is an instruction-following model introduced by Stanford researchers. Impressively, with only $600 of compute spend, the researchers demonstrated that on qualitative benchmarks Alpaca performed similarly to OpenAI's text-davinci-003, a significantly larger model.
Orca is a descendant of LLaMA developed by Microsoft with finetuning on explanation traces obtained from GPT-4.
Orca-13B is a LLM developed by Microsoft. It is based on LLaMA with finetuning on complex explanation traces obtained from GPT-4. By using rich signals, Orca surpasses the performance of models such as Vicuna-13B on complex tasks. However, given its model backbone and the data used for its finetuning, Orca is under noncommercial use.
Further reading