Over the years, numerous commercial (e.g., iCon , Omega , ConfGen , MOE , CREST ) and open-source tools (e.g., FROG2 , Confab , OpenBabel , and RDKit ) have been developed for the purpose of fast and accurate conformer generation. Most recently, Seidel et al. and earlier Friedrich et al. reviewed some of these software's performance. Due to the enormous number of conformer calculations, most of the algorithms use molecular mechanics (MM) based minima search rather than more accurate QM methods. Searching for minima using MM methods brings additional problems. First, they rely on the accuracy of the force field (FF) used and to cover all chemical library, they need to be generalized (such as UFF, GAFF, MMFF94), which results in losing accuracy. Second, they use empirical parameters for bonds, angles, and dihedral definition for the covalent interactions as well as fixed partial atomic charges and Lennard-Jones parameters for the non-covalent interactions. They require well-defined bonding information at the initial structure. If the initial structure is somehow mis-drawn or the preassigned bond order is incorrect, the MM based minimization algorithms might totally fail locating the correct nearest minimum and the other minima. Furthermore, even if the bonding is given correctly and the local minimum is in the correct conformation, the relative energies are still in MM level, which might deviate from the actual values. For these reasons, there is a need for performing minimizations and searching for conformers at the QM accuracy. Searching for global and local minima using QM methods such as DFT can become computationally too costly due to the enormous number of conformation evaluations.