I assume 2 things (1) you're comparing the t distribution to the normal distribution (2) you meant 95% confidence interval (as 1.96 is the critical value for a 95% CI of a normal distribution) he sample size determines these values. Because the variance of the sample is unknown it is estimated from the sample. This cause the tails of the t distribution to be heavier than a normal distribution at lower sample sizes. At larger sample sizes (say 150+) the critical value at the 95% (I think this is what you meant) is closer to the normal distribution (pretty much aproximates it) as seen below.

Code:`> sample_size <- 150 > df <- sample_size - 2 > df [1] 148 > qt(.95, df) [1] 1.655215`