Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide, ranking first in the global disease burden. Evidence on association between temperature and cardiovascular disease is insufficient and inconsistent in developing countries. In this study, a distributed lag nonlinear model (DLNM) was used to determine the association between daily mean temperature and cardiovascular diseases (CVD) related admission in Lanzhou 2015–2019. We included 41,389 patients with CVD in this study. The relative risk (RR) of CVD admission increased significantly with temperature in lag 5–10 days, and we found harvesting effect of temperature in the study, shown as decreased RR in lag 15–30 days. The maximum RR was 1.15 (95% confidence interval [CI]: 1.03–1.30), corresponding to 24 °C. Both cold and heat effects of temperature could impact the CVD admission. Compared with the 25th percentile of temperature (2 °C), the cumulative relative risk (cumRR) of extreme cold (−5 °C, the 2.5th percentile of the temperature) was 0.69 (95% CI: 0.51–0.94) in lag 0–14, whereas the cumRR of moderate cold (−2 °C, the 10th percentile) was 0.83 (95% CI:0.71–0.97). Compared with the 75th percentile of temperature (20-°C), the cumRR of extreme heat (27 °C, the 97.5th percentile) was 0.93 (95% CI: 0.78–1.10) in lag 0, whereas the cumRR of moderate heat (24 °C, the 90th percentile) was 1.01 (95% CI: 0.94–1.08). In the stratified analysis, cold decreased RR significantly in female and ≥65 years, whereas heat increased it more obviously in male and ≥65 years. Ambient temperature and CVD admissions were positively associated, with the harvesting effect. Our findings demonstrate the adaption of residents in Lanzhou to cold temperature. Public and environmental policies and measures aimed at moderate heat may minimize CVD burden effectively.