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Description: We describe and test a simple sequential sampling model of N-choice speeded decision making: the racing diffusion model. The model makes speeded decisions from a race of evidence accumulators that integrate information in a noisy fashion within a trial. Unlike many current sequential sampling models, the racing diffusion does not assume that evidence accumulation rate varies between trial, and so, the model provides alternative explanations of key response time (RT) phenomena, such as fast and slow error RTs relative to correct RTs. Applying the racing diffusion model is relatively fast and easy given the analytic solution to the likelihood of response times, yet the model contains processing dynamics that may be of interest to cognitive-neuroscientist. The racing diffusion is an alternative to simple sequential sampling models that do without within-trial drift variability and complex models that include this variability, but are difficult to implement.