This paper is concerned with the estimation of the volatility process in a stochastic volatility model of the following form: $dX_t=a_tdt+sigma_tdW_t$, where $X$ denotes the log-price and $sigma$ is a c`adl`ag semi-martingale. In the spirit of a series of recent works on the estimation of the cumulated volatility, we here focus on the instantaneous volatility for which we study estimators built as finite differences of the textit{power variations} of the log-price. We provide central limit theorems with an optimal rate depending on the local behavior of $sigma$. In particular, these theorems yield some confidence intervals for $sigma_t$.