* '''General Parallelism:''' Chapel has the goal of supporting any parallel algorithm you can conceive of on any parallel hardware you want to target. In particular, you should never hit a point where you think “Well, that was fun while it lasted, but now that I want to do x, I’d better go back to MPI.”

* '''Separation of Parallelism and Locality:''' Chapel supports distinct concepts for describing parallelism (“These things should run concurrently”) from locality (“This should be placed here; that should be placed over there”). This is in sharp contrast to conventional approaches that either conflate the two concepts or ignore locality altogether.

* '''Multiresolution Design:''' Chapel is designed to support programming at higher or lower levels, as required by the programmer. Moreover, higher-level features—like data distributions or parallel loop schedules—may be specified by advanced programmers within the language.

* '''Productivity Features:''' In addition to all of its features designed for supercomputers, Chapel also includes a number of sequential language features designed for productive programming. Examples include type inference, iterator functions, object-oriented programming, and a rich set of array types. The result combines productivity features as in Python™, Matlab®, or Java™ software with optimization opportunities as in Fortran or C.