diff --git a/src/host/sparse.jl b/src/host/sparse.jl
index c5608b9d..349e1f18 100644
--- a/src/host/sparse.jl
+++ b/src/host/sparse.jl
@@ -670,7 +670,6 @@ end
     if leading_dim ≤ leading_dim_size
         iter = @inbounds iter_type(T, Ti)(leading_dim, args...)
 
-
         output_ptrs  = output isa GPUSparseDeviceMatrixCSR ? output.rowPtr : output.colPtr
         output_ivals = output isa GPUSparseDeviceMatrixCSR ? output.colVal : output.rowVal
         # fetch the row offset, and write it to the output
@@ -691,7 +690,6 @@ end
                 ptr = @inbounds ptrs[i]
                 _getindex(arg, I, ptr)
             end
-
             @inbounds output_ivals[output_ptr] = sub_leading_dim
             @inbounds output.nzVal[output_ptr] = f(vals...)
             output_ptr += one(Ti)
@@ -903,7 +901,13 @@ function Broadcast.copy(bc::Broadcasted{<:Union{GPUSparseVecStyle,GPUSparseMatSt
     if output isa AbstractGPUSparseArray
         args   = (bc.f, output, offsets, bc.args...)
         kernel = sparse_to_sparse_broadcast_kernel(get_backend(bc.args[first(sparse_args)]))
-        ndrange = output.nnz
+        ndrange = if sparse_typ <: AbstractGPUSparseVector
+                    output.nnz
+                  elseif sparse_typ <: AbstractGPUSparseMatrixCSC
+                    size(output, 2)
+                  else
+                     size(output, 1)
+                  end
     else
         args   = sparse_typ <: AbstractGPUSparseVector ? (sparse_typ, bc.f, output, offsets, bc.args...) :
                                                          (sparse_typ, bc.f, output, bc.args...)
diff --git a/test/testsuite/sparse.jl b/test/testsuite/sparse.jl
index a31abe6d..3e0d92fe 100644
--- a/test/testsuite/sparse.jl
+++ b/test/testsuite/sparse.jl
@@ -283,6 +283,19 @@ function broadcasting_matrix(AT, eltypes)
             dz = dx .* dy .* dw
             @test dz isa AT{ET}
             @test z == SparseMatrixCSC(dz)
+
+            # create a matrix with nnz < leading_dim
+            x = spdiagm(m, m, 2=>rand(ET, m - 2))
+            dx = AT(x)
+            y = ET(3) * x
+            dy = ET(3) * dx
+            @test y == SparseMatrixCSC(dy)
+
+            x = spdiagm(m, m, -2=>rand(ET, m - 2))
+            dx = AT(x)
+            y = ET(3) * x
+            dy = ET(3) * dx
+            @test y == SparseMatrixCSC(dy)
         end
     end
 end