Most existing models of infectious diseases, including tuberculosis (TB), do not allow end-users to customize results to local conditions. We created a dynamic transmission model to project TB incidence, TB mortality, multidrug-resistant (MDR) TB prevalence, and incremental costs over five years after scale-up of nine alternative diagnostic strategies including combinations of sputum smear microscopy, Xpert MTB/RIF, microcolony-based culture, and same-day diagnosis. We developed a corresponding web-based interface that allows users to specify local costs and epidemiology. Full model code - including the ability to change any input parameter - is also included. The impact of improved diagnostic testing was greater for mortality and MDR-TB prevalence than TB incidence, and was maximized in high-incidence, low-HIV settings. More costly interventions generally had greater impact. In settings with little capacity for up-front investment, same-day microscopy had greatest impact on TB incidence and became cost-saving within five years if feasible to deliver at $10/test. In settings where more initial investment was possible, population-level scale-up of either Xpert MTB/RIF or microcolony-based culture offered substantially greater benefits, often averting ten times more TB cases than narrowly-targeted diagnostic strategies at minimal incremental long-term cost. Where containing MDR-TB is the overriding concern, Xpert for smear-positives has reasonable impact on MDR-TB incidence, but at substantial price and little impact on overall TB incidence and mortality. This novel, user-friendly modeling framework improves decision-makers' ability to evaluate the impact of TB diagnostic strategies, accounting for local conditions.