Binomial distribution: Cumulative distribution vs Chernoff bound

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I am studying Chernoff bounds lately but I am not clear how this is better than cumulative distribution function for binomial distribution.

For example, let's say that p = 0.3 and n = 3. I am interested in finding $Pr(X \geq 2)$.

If I do cumulative distribution, this will be P(X = 2) + P(X = 3), and the answer comes out to be 0.21.

But when I apply Chernoff bound for $Pr(X \geq 2)$, I get an upper bound of 0.6. How is Chernoff bound any useful then? Why not just use cumulative distribution always as it seems to give better bounds. What am I missing?

(I used this to find the Chernoff bound)