The changing climate poses a growing challenge to the population health. The objective of this study was to assess the association between ambient temperature and cause-specific mortality in Suzhou. Based on the non-accidental mortality data collected during 2008–2022 in Suzhou, China, this study utilized an individual-level case-crossover design to evaluate the associations of temperature with cause-specific mortality. We applied a distributed lag nonlinear model with a maximum lag of 14 days to account for lag effects. Mortality risk due to extreme cold (<2.5th percentile) and extreme heat (>97.5th percentile) was analyzed. A total of 634,530 non-accidental deaths were analyzed in this study. An inverse J-shaped exposure-response relationship was observed between ambient temperature and non-accidental mortality, with the minimum mortality temperature (MMT) at 29.1℃. The relative risk (RR) of mortality associated with extreme cold (2.5th percentile) was 1.37 [95 % confidence interval (CI): 1.30, 1.44], higher than estimate of 1.09 (95 %CI: 1.07, 1.11) for extreme heat (97.5th percentile) relative to the MMT. Heat effect lasted for 2–3 days, while cold effect could persist for almost 14 days. Higher mortality risk estimates were observed for cardiorespiratory deaths compared to total deaths, with statistically significant between-group differences. Consequently, this study provides first-hand evidence on the associations between ambient temperatures and mortality risks from various causes, which could help local government and policy-makers in designing targeted strategies and public health measures against the menace of climate change.