Llama and GPT are auto-regressive decoder only architectures which for pure translation jobs are not the optimal architectures. Training seq2seq models or encoder/decoder models on datasets of sentence pairs designed for translation will likely allow you to use much smaller models. You will not be wasting parameters on general “language understanding” capability that Llama and GPT have if pure translation is all you need. T5 or Flan-T5 might be good starting points.