A content-balancing accuracy index, called q₉, to evaluate gene-finding algorithms has been proposed. Here the concept of content-balancing means that the evaluation by this index is independent of the coding and non-coding composition of the sequence being evaluated. Since the coding and non-coding compositions are severely unbalanced in eukaryotic genomes, the performance of gene-finding algorithms is either over- or under-evaluated by the widely used accuracy indices, e.g., the correlation coefficient, due to the lack of content-balancing ability. Using the new accuracy index q₉, seven gene-finding algorithms, FGENES; Gene-Mark.hmm; Genie; Genescan; HMMgene; Morgan and MZEF, were compared and evaluated. It is shown that Genescan is still the best one, but with q₉= 89%, averaged over the prediction for 195 sequences. In addition to the content-balancing ability, q₉ has the merit of having definition in all possible cases. It is also shown that the traditional specificity s_p carries important information on the performance of the algorithm being evaluated. The set of sensitivity s_n, specificity s_p and the accuracy q₉ constitutes a complete kit to evaluate gene-finding algorithms at nucleotide level. In addition, a graphic method to compare and evaluate gene-finding algorithms has been proposed, too. Its major advantage is that the overall performance of algorithms can be grasped quickly in a perceivable form. Additionally, the new accuracy index q₉ may be applied to evaluate the performance of weather forecast, clinical diagnosis, psychological examination and protein secondary structure prediction etc.