diff --git a/src/dual.jl b/src/dual.jl
index 31a7ce99..f2c33bf7 100644
--- a/src/dual.jl
+++ b/src/dual.jl
@@ -658,6 +658,12 @@ function LinearAlgebra.eigvals(A::Symmetric{<:Dual{Tg,T,N}}) where {Tg,T<:Real,N
     Dual{Tg}.(λ, tuple.(parts...))
 end
 
+function LinearAlgebra.eigvals(A::Symmetric{<:Dual{Tg,T,N}, <:StaticArrays.StaticMatrix}) where {Tg,T<:Real,N}
+    λ,Q = eigen(Symmetric(value.(parent(A))))
+    parts = ntuple(j -> diag(Q' * getindex.(partials.(A), j) * Q), N)
+    Dual{Tg}.(λ, tuple.(parts...))
+end
+
 function LinearAlgebra.eigvals(A::Hermitian{<:Complex{<:Dual{Tg,T,N}}}) where {Tg,T<:Real,N}
     λ,Q = eigen(Hermitian(value.(real.(parent(A))) .+ im .* value.(imag.(parent(A)))))
     parts = ntuple(j -> diag(real.(Q' * (getindex.(partials.(real.(A)) .+ im .* partials.(imag.(A)), j)) * Q)), N)
@@ -682,7 +688,14 @@ end
 
 function LinearAlgebra.eigen(A::Symmetric{<:Dual{Tg,T,N}}) where {Tg,T<:Real,N}
     λ = eigvals(A)
-    _,Q = eigen(SymTridiagonal(value.(parent(A).dv),value.(parent(A).ev)))
+    _,Q = eigen(Symmetric(value.(parent(A))))
+    parts = ntuple(j -> Q*_lyap_div!(Q' * getindex.(partials.(A), j) * Q - Diagonal(getindex.(partials.(λ), j)), value.(λ)), N)
+    Eigen(λ,Dual{Tg}.(Q, tuple.(parts...)))
+end
+
+function LinearAlgebra.eigen(A::Symmetric{<:Dual{Tg,T,N}, <:StaticArrays.StaticMatrix}) where {Tg,T<:Real,N}
+    λ = eigvals(A)
+    _,Q = eigen(Symmetric(value.(parent(A))))
     parts = ntuple(j -> Q*_lyap_div!(Q' * getindex.(partials.(A), j) * Q - Diagonal(getindex.(partials.(λ), j)), value.(λ)), N)
     Eigen(λ,Dual{Tg}.(Q, tuple.(parts...)))
 end
diff --git a/test/JacobianTest.jl b/test/JacobianTest.jl
index 9ea3b0a7..69f9409c 100644
--- a/test/JacobianTest.jl
+++ b/test/JacobianTest.jl
@@ -235,6 +235,14 @@ end
 @testset "eigen" begin
     @test ForwardDiff.jacobian(x -> eigvals(SymTridiagonal(x, x[1:end-1])), [1.,2.]) ≈ [(1 - 3/sqrt(5))/2 (1 - 1/sqrt(5))/2 ; (1 + 3/sqrt(5))/2 (1 + 1/sqrt(5))/2]
     @test ForwardDiff.jacobian(x -> eigvals(Symmetric(x*x')), [1.,2.]) ≈ [0 0; 2 4]
+    
+    x0 = [1.0, 2.0];
+    ev1(x) = eigen(Symmetric(x*x')).vectors[:,1]
+    @test ForwardDiff.jacobian(ev1, x0) ≈ Calculus.finite_difference_jacobian(ev1, x0)
+    ev2(x) = eigen(SymTridiagonal(x, x[1:end-1])).vectors[:,1]
+    @test ForwardDiff.jacobian(ev2, x0) ≈ Calculus.finite_difference_jacobian(ev2, x0)
+    x0_static = SVector{2}(x0)
+    @test ForwardDiff.jacobian(ev1, x0_static) ≈ Calculus.finite_difference_jacobian(ev1, x0)
 end
 
 @testset "type stability" begin