We investigate the tail asymptotics of the response time distribution for the cancel-on-start (c.o.s.) and cancel-on-completion (c.o.c.) variants of redundancy-d scheduling and the fork–join model with heavy-tailed job sizes. We present bounds, which only differ in the pre-factor, for the tail probability of the response time in the case of the first-come first-served discipline. For the c.o.s. variant, we restrict ourselves to redundancy-d scheduling, which is a special case of the fork–join model. In particular, for regularly varying job sizes with tail index-$$\nu $$ ν the tail index of the response time for the c.o.s. variant of redundancy-d equals -$$\min \{d_{\mathrm {cap}}(\nu -1),\nu \}$$ min { d cap ( ν - 1 ) , ν } , where $$d_{\mathrm {cap}} = \min \{d,N-k\}$$ d cap = min { d , N - k } , N is the number of servers and k is the integer part of the load. This result indicates that for $$d_{\mathrm {cap}} < \frac{\nu }{\nu -1}$$ d cap < ν ν - 1 the waiting time component is dominant, whereas for $$d_{\mathrm {cap}} > \frac{\nu }{\nu -1}$$ d cap > ν ν - 1 the job size component is dominant. Thus, having $$d = \lceil \min \{\frac{\nu }{\nu -1},N-k\} \rceil $$ d = ⌈ min { ν ν - 1 , N - k } ⌉ replicas is sufficient to achieve the optimal asymptotic tail behavior of the response time. For the c.o.c. variant of the fork–join ($$n_{\mathrm {F}},n_{\mathrm {J}}$$ n F , n J ) model, the tail index of the response time, under some assumptions on the load, equals $$1-\nu $$ 1 - ν and $$1-(n_{\mathrm {F}}+1-n_{\mathrm {J}})\nu $$ 1 - ( n F + 1 - n J ) ν , for identical and i.i.d. replicas, respectively; here, the waiting time component is always dominant.