In this article, we consider the following class of stochastic partial differential equations (SPDE): \begin{equation*} \left{\begin{aligned} (t)&=(t,(t)) t+(t,(t))(t)+\int_{}γ(t,(t-),z)\widetildeπ( t, z),; t\in[0,T],\ (0)&=\boldsymbol{x} \in ,\end{aligned} \right.\end{equation*} with fully locally monotone coefficients in a Gelfand triplet , where the mappings \begin{align*} :[0,T]\times \to^,\quad :[0,T]\times \to_2(,), \quad γ:[0,T]\times\times\to, \end{align} are measurable, is the space of all Hilbert-Schmidt operators from , is a -cylindrical Wiener process and is a compensated time homogeneous Poisson random measure. Such kind of SPDE cover a large class of quasilinear SPDE and a good number of fluid dynamic models. Under certain generic assumptions of and , using the classical Faedo-Galekin technique, a compactness method and a version of Skorokhod’s representation theorem, we prove the existence of a \emph{probabilistic weak solution} as well as \emph{pathwise uniqueness of solution}. We use the classical Yamada-Watanabe theorem to obtain the existence of a \emph{unique probabilistic strong solution}. Finally, we allow both diffusion coefficient and jump noise coefficient to depend on both -norm and -norm, which implies that both the coefficients could also depend on the gradient of solution. We establish the global solvability results.

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