diff -up src/sage/numerical/backends/cvxopt_backend.pyx.orig src/sage/numerical/backends/cvxopt_backend.pyx
--- src/sage/numerical/backends/cvxopt_backend.pyx.orig	2021-05-09 16:00:11.000000000 -0600
+++ src/sage/numerical/backends/cvxopt_backend.pyx	2021-05-28 12:05:47.551650940 -0600
@@ -550,7 +550,7 @@ cdef class CVXOPTBackend(GenericBackend)
         self.answer = solvers.lp(c,G,h)
 
         #possible outcomes
-        if self.answer['status'] == 'optimized':
+        if self.answer['status'] in ['optimized', 'optimal']:
             pass
         elif self.answer['status'] == 'primal infeasible':
             raise MIPSolverException("CVXOPT: primal infeasible")
diff -up src/sage/numerical/backends/cvxopt_sdp_backend.pyx.orig src/sage/numerical/backends/cvxopt_sdp_backend.pyx
--- src/sage/numerical/backends/cvxopt_sdp_backend.pyx.orig	2021-05-09 16:00:11.000000000 -0600
+++ src/sage/numerical/backends/cvxopt_sdp_backend.pyx	2021-05-28 12:05:47.552650940 -0600
@@ -150,7 +150,7 @@ cdef class CVXOPTSDPBackend(MatrixSDPBac
         self.answer = solvers.sdp(c,Gs=G_matrix,hs=h_matrix)
 
         #possible outcomes
-        if self.answer['status'] == 'optimized':
+        if self.answer['status'] in ['optimized', 'optimal']:
             pass
         elif self.answer['status'] == 'primal infeasible':
             raise SDPSolverException("CVXOPT: primal infeasible")