To effectively reduce the high energy consumption and high carbon emission generated in the fresh produce distribution process, a fresh product multi-temperature low-carbon co-distribution path optimization model is constructed under the constraints of the time window and vehicle-rated load to minimize the total cost of distribution, and the impact of vehicle travel speed, distance, and weight on carbon emission is comprehensively considered in the model. Based on the genetic algorithm, the model is solved by appling the improved sequential crossover method. The validity of the model and algorithm is verified by the example, and the comparative analysis shows that the multi-temperature low-carbon variable-speed co-distribution path is better, and the total distribution cost is reduced by 11.2%, among which, the carbon emission cost is reduced by 5.2%. The multi-temperature low-carbon variable speed co-allocation model for fresh produce has obvious advantages compared with the average speed, which can provide a methodological reference for other logistics distribution studies.