As one of the most important essentials of CPU, mathematical function libraries play a key role in scientific and engineering computing with high performance computers. Existing testing techniques and platforms can only evaluate function libraries from one or two aspects, therefore are unable to provide an evaluation result as a whole picture. Consequently, they are applicable for a specific targeting architecture and the scalability is restricted. To address this problem, this study proposes a novel testing platform BMltest (Basic math library test). It constructs the testing suite, which is composed of eigenvalues, IEEE-754 special values and IEEE-754 normalized values, to improve the cover rate of the floating numbers. A MPFR (multiple-precision floating-point reliable library) based precision test is introduced, and as a result, the reliability is improved. A code isolation based performance test is also described, so as to further eliminate the impact from enclosing circumstance. Some practical evaluating strategies are proposed to evaluate the test result. Such design makes the testing suite not correlated to mathematical functions, thereby ensuring the applicability. The experimental results show that, by testing 855 functions from various libraries, including GNU, Open64 and Mlib, the testing suite provided by BMltest is more efficient and the precision test is more reliable. At the same time, compared with those of other testing platforms, the performance test is more stable.