It's very clear that the current Bard model is weaker than the largest PaLM 2 model. But for certain things, Bard seems worse than even the smallest model described. It's hard to say without someone doing a comprehensive benchmark, but the artifically limited context size makes testing useless for data.

The model was surprisingly confident when I tried to ask it about the relationship between better language comprehension and parameter size. The coherence displayed by the model, when it argued that a smaller model size will be capable of matching and surpassing competitive model performance, was a little jarring. Especially when, in the question right before, it said that the large PaLM 2 model has 540 trillion parameters.