The unknown emissivity of materials is a big obstacle to radiation true temperature measurement, which leads to the fact that the true temperature of materials cannot be obtained by a single group of measurement data. People can only calculate the non-true temperature, such as brightness temperature, by assuming the emissivity model of materials. Based on this background, Gardner J and other scientists put forward multispectral thermometry and constantly improve its theory. Nowadays, multispectral thermometry is widely used in high-temperature and ultra-high temperature measurement, high temperature target thermal performance measurement, true temperature dynamic measurement, etc. In 2005, Sun Xiaogang put forward the second measurement method. The secondary measurement method is a kind of multispectral true temperature inversion algorithm, which solves the problem of inversion of true temperature and material emissivity under each wavelength by the iterative operation between two groups of measurement data. It ensures the accuracy of the emissivity and true temperature results under each wavelength by building quantities of emissivity models. However, it needs to build a large number of emissivity models in the mathematical operation and software operation. By matching all emissivity models, the best solution of true temperature is obtained, which not only consumes a lot of time but also takes up a lot of software resources. In this paper, a new fast inversion method of true multispectral temperature is proposed. This paper first reveals the inequality equations between radiational signals and emissivity and then adds the steps of optimizing the emissivity model library in the algorithm of the secondary measurement method. This measure can screen out the unreasonable models in the emissivity model library to reduce the scale of the emissivity model library, saving a lot of calculation time and software resources. This paper carries out the simulation experiment of wavelength in 0.400~1.100 μm, which contains six initial emissivity models.The results of the fast inversion method of true multispectral temperature and secondary measurement method are compared, and the results show that the fast inversion method of true multispectral temperature not only guarantees the inversion accuracy but also reduces calculation time compared with the second measurement method for the same target under the same initial temperature value and same emissivity search range. The fast inversion method of true multispectral temperature reduces 29%~64% emissivity model number and 26%~57% calculation time. After that, this paper carries out the actual experiment of wavelength in 0.574~0.914 μm. The results show that under the same conditions, the fast inversion method of true multispectral temperature can reduce the emissivity model number by 42%~48% and reduce the calculation time by 35%~49% compared with the second measurement method on the premise of ensuring accuracy. The above experiments show that the fast inversion method of true multispectral temperature is feasible, and it has important value for large-scale multispectral true temperature measurement technology and online multispectral true temperature measurement technology.