Which is more efficient to use in a for loop, i<sqrt(n) or i*i<(n)?

Can anyone help me out which of the following two is more efficient and correct?

1.

for(int i = num; i * i <= n; i++)

2.

int root = sqrt(n);
for(int i = num; i <= root; i++)

In the first approach we are calculating square of i each time loop runs. Also we can't pre-compute square of i as i gets updated each time.

In the second approach we are not calculating sqrt(n) each time. Is this saving time?

Will the 2nd loop work faster with 100% accurate result even for large numbers (like 10^6)?

It makes sense that the second scenario should be more effective as the loop limiter need not be calculated for every iteration in the loop. Tried to measure the CPU time used in going thru the 2 types of for loops with the code given below. Looks like the cpu time is actually lesser for the first scenario for smaller numbers like n=25. but then for values n>=100 the second scenario gives a smaller cpu time.

    clock_t start,end;
    double cpu_time_used;
    double n, root;

    n = atoi(argv[1]);
    printf("n= %0f \n",n);
    start = clock();
    for (int i=0; i*i<n; i++);
    end = clock();
    cpu_time_used = ((double) (end-start)) / CLOCKS_PER_SEC;
    printf("first iter: cpu_time_used: %f \n", cpu_time_used);

    start = clock();
    root = sqrt(n);
    for (int i=0; i<=root; i++);
    end = clock();
    cpu_time_used = ((double) (end-start)) / CLOCKS_PER_SEC;
    printf("second iter: cpu_time_used: %f \n", cpu_time_used);

Outputs:

n= 25.000000 
first iter: cpu_time_used: 0.000004 
second iter: cpu_time_used: 0.000011 

n= 100.000000 
first iter: cpu_time_used: 0.000002 
second iter: cpu_time_used: 0.000001 

n= 1000000.000000 
first iter: cpu_time_used: 0.000011 
second iter: cpu_time_used: 0.000008