The Lanczos algorithm is increasingly used for model reduction of large scale stable systems. Two features of the algorithm, however, limit its applicability: the tendency of the reduced model to poorly approximate low frequency dynamics, and the fact that the approximation is not guaranteed to be stable. This paper tackles these issues via a computationally efficient implicit restart scheme based on balanced truncation which preserves the attractive features of the Lanczos algorithm.