Intermittency is an important metric for determining the likelihood of extreme values of ﬂuctuating quantities such as temperature gradients and vorticity in premixed turbulent ﬂames. Such extreme values can lead to ﬂow-altering events including extinction, auto- and re-ignition, and deﬂagration to detonation transition. In this study, we use a conditional probability density function (PDF) approach to analyze intermittency of enstrophy (i.e., vorticity magnitude) and temperature gradient magnitude ﬁelds. The analysis is based on data from direct numerical simulations (DNS) of stoichiometric premixed hydrogen-air ﬂames in unconﬁned domains. The DNS are performed for a range of scenarios, including both single- and multi-step chemistry models, temperature-dependent and constant viscosities, different turbulence intensities, and two different resolutions. In each case, conditional PDFs are generated using a temperature-based progress variable in order to characterize intermittency at different locations within the ﬂame. We show that intermittency in the scalar gradient magnitude is most strongly inﬂuenced by the turbulence intensity and the choice of chemistry model, while enstrophy intermittency is most strongly dependent on intensity and temperature dependence of the viscosity, with little dependence on chemistry.