SMC-ABC is for those model that you can simulate “fake” observation, but cannot compute likelihood (or likelihood evaluation is too expensive). You can use summary statistics which I guess what you mean by evaluating the likelihood for all data point instead of each observed independently
In terms of performance, I would say SMC-ABC is less well-tuned like NUTS, so you should spend time to evaluate the inference output using Posterior predictive check to make sure the output makes sense.