The last decade progresses have led the Satisfiability Problem (SAT) to be a great and competitive practical approach to solve a wide range of industrial and academic problems. Thanks to these progresses, the size and difficulty of the SAT instances has grown significantly. Among the recent solvers, a few are parallel and most of them use the message passing paradigm. In a previous work by Vander-Swalmen et al. (IWOMP, 146–157, 2008), we presented a fine grain parallel SAT solver designed for shared memory using OPENMP and named MTSS, for Multi Threaded Sat Solver. MTSS extends the “guiding path” notion and uses a collaborative approach where a rich thread is in charge of the search-tree evaluation and where a set of poor threads yield logical or heuristics information to simplify the rich task. In this paper, we extend the poor thread abilities of MTSS and present extensive comparative results on random 3-SAT problems. These new experimentations show that fine grained techniques associated to poor tasks within the framework of MTSS can achieve very interesting speedup on multi-core processors.