For the first two queries all it has to do is scan down the clustered index to the first entry for that value of IDUkazatel - because of the order of the index that row will be the lowest value for cas for that value of IDUkazatel.

In the second query this optimisation is not value and it is probably seeking to the first row for IDUkazatel=24 then scanning down the index until the last row with IDUkazatel=25 to find the minimum value of `cas` over all those rows.

If you hover over that fat arrow you'll see it is reading many rows (certainly all those for 24, probably all those for 25 too), where as the thin arrows in the plan output for the other two show the `top` action causing it to only consider one row.

You could try run each query and then get the minimum for the minimums found:

    SELECT MIN(cas)
    FROM   (
            SELECT cas=MIN(cas) FROM PenData p WHERE p.IDUkazatel = 24
            UNION ALL
            SELECT cas=MIN(cas) FROM PenData p WHERE p.IDUkazatel = 25
        ) AS minimums

Or perhaps cleaner, adding a group by may give the query planner the clue that it only needs to care about one row per value:

    SELECT MIN(cas)
    FROM   (
            SELECT IDUkazatel, cas=MIN(cas) FROM PenData p WHERE p.IDUkazatel IN (24, 25) GROUP BY IDUkazatel
        ) AS minimums

(I've not generated data and tried these queries - run them on your data to see if they result in a better query plan)

Another option that might help is an index over `cas` (or maybe `cas, IDUkazatel`). That way with your original query it can scan down this index until it finds the first row where IDUkazatel is 24 or 25, though depending on the spread of data this may be worse (many values for IDUkazatel then it may have to scan quite for to find the first values it cares about, if there are few then it will probably find the relevant one relatively quickly.