In your example, you would reject the first seven. The BH procedure is a step-up procedure: after ordering your pvalues as $p_1,\dots,p_m$, you should take the last $k$ such that $p_k \leq \frac{k}{m}\alpha$ regardless of whether you have some $p_{k'}$'s with $k'<k$ that do not satisfy this.
Maybe someone else can do a better job of providing intuition, but here's how I think of it. The TL;DR is that what you observed actually happens quite often, and this is perfectly all right: we order the $p_k$'s to get the inverse CDF so that we can approximate the FDR, there is nothing inherently important about the ordering necessarily except that it is computationally easy... we really just need to calculate $\hat{F}_m(u)$, which approximates the (unknown) distribution of the pvalues, and the method you take by ordering does this quickly and easily. To expand on this:
BH works in the following way: suppose you have $\pi$ tests that do reject the null, and thus $1-\pi$ tests that are truly null. Under the null, a pvalue $p$ is uniformly distributed, and so F_{null}(u) = u. The distribution of pvalues that are under the false null have some unknown distribution $F_{notnull}(u)$. Then the distribution of pvalues $p$ is
$$F(u) = (1-\pi)F_{null}(u) + \pi F_{nonnull}(u) = (1-\pi)u + \pi F_{nonnull}(u)$$
You can show that for any level $u$ (let me know if you want a proof of this, but it can probably be found online),
$$FDR(u) \approx \frac{(1-\pi)u}{F(u)}$$
and the whole point of FDR is that we want to find $u$ so that $FDR(u) = \alpha$ (which is precisely setting the FDR to level $\alpha$.
We don't know $F(u)$, so we approximate it by ordering the $p_k$'s and have
$$\hat{F}_m(u) = \frac{1}{m} \sum_i 1\{P_i\leq u\}$$
and when we ignore ties (it's easy to adjust for this so it makes no difference, pvalues are continuous, so youll always have some difference between them in reality, and your example still holds if you add some small perturbation and re-order), we have $\hat{F}_m(P_i) = \frac{i}{m}$.
We also don't know $\pi$, so we conservatively set it to $\pi = 0$. Then we have that we want the $p_i$ so that
\begin{align*}
\alpha = FDR(p_i) & \approx \frac{p_i}{\hat{F}_m(u)} \\
& = \frac{p_im}{i} \\
\end{align*}
and so we want $p_i$ so that $\alpha\frac{i}{m} = p_i$ (or realistically, we want to get as close as possible to this, so we take the max $i$ so that $\alpha\frac{i}{m} \geq p_i$ and reject all the ones below this $p_i$, and so we really don't care about anything before this value.
