diff --git a/NDTensors/src/dense/dense.jl b/NDTensors/src/dense/dense.jl
index 1c41553eb2..39b6dadecf 100644
--- a/NDTensors/src/dense/dense.jl
+++ b/NDTensors/src/dense/dense.jl
@@ -123,7 +123,7 @@ function promote_rule(
   ::Type{<:Dense{ElT1,DataT1}}, ::Type{<:Dense{ElT2,DataT2}}
 ) where {ElT1,DataT1,ElT2,DataT2}
   ElR = promote_type(ElT1, ElT2)
-  VecR = promote_type(DataT1, DataT2)
+  VecR = promote_type(unwrap_type(DataT1), unwrap_type(DataT2))
   VecR = similartype(VecR, ElR)
   return Dense{ElR,VecR}
 end
diff --git a/NDTensors/test/diag.jl b/NDTensors/test/diag.jl
index 8422082e92..a712afbc70 100644
--- a/NDTensors/test/diag.jl
+++ b/NDTensors/test/diag.jl
@@ -4,31 +4,43 @@ using Test
 @testset "DiagTensor basic functionality" begin
   include("device_list.jl")
   devs = devices_list(copy(ARGS))
-  @testset "test device: $dev" for dev in devs
-    t = dev(tensor(Diag(rand(ComplexF64, 100)), (100, 100)))
+  @testset "test device: $dev" for dev in devs,
+    elt in (Float32, ComplexF32, Float64, ComplexF64)
+
+    if dev == NDTensors.mtl && real(elt) ≠ Float32
+      # Metal doesn't support double precision
+      continue
+    end
+    t = dev(tensor(Diag(rand(elt, 100)), (100, 100)))
     @test conj(data(store(t))) == data(store(conj(t)))
     @test typeof(conj(t)) <: DiagTensor
 
-    d = rand(Float32, 10)
-    D = dev(Diag{ComplexF64}(d))
-    @test eltype(D) == ComplexF64
-    @test dev(Array(dense(D))) == convert.(ComplexF64, d)
+    d = rand(real(elt), 10)
+    D = dev(Diag{elt}(d))
+    @test eltype(D) == elt
+    @test dev(Array(dense(D))) == convert.(elt, d)
     simD = similar(D)
     @test length(simD) == length(D)
     @test eltype(simD) == eltype(D)
-    D = dev(Diag(1.0))
-    @test eltype(D) == Float64
-    @test complex(D) == Diag(one(ComplexF64))
+    D = dev(Diag(one(elt)))
+    @test eltype(D) == elt
+    @test complex(D) == Diag(one(complex(elt)))
     @test similar(D) == Diag(0.0)
 
     D = Tensor(Diag(1), (2, 2))
     @test norm(D) == √2
     d = 3
-    vr = rand(d)
+    vr = rand(elt, d)
     D = dev(tensor(Diag(vr), (d, d)))
     @test Array(D) == NDTensors.LinearAlgebra.diagm(0 => vr)
     @test matrix(D) == NDTensors.LinearAlgebra.diagm(0 => vr)
     @test permutedims(D, (2, 1)) == D
+
+    # Regression test for https://github.com/ITensor/ITensors.jl/issues/1199
+    S = dev(tensor(Diag(randn(elt, 2)), (2, 2)))
+    V = dev(tensor(Dense(randn(elt, 12, 2)'), (3, 4, 2)))
+    @test contract(S, (2, -1), V, (3, 4, -1)) ≈
+      contract(dense(S), (2, -1), copy(V), (3, 4, -1))
   end
 end
 @testset "DiagTensor contractions" begin