diff --git a/src/lib/broadcast.jl b/src/lib/broadcast.jl
index 8694b394c..df9fdc9b5 100644
--- a/src/lib/broadcast.jl
+++ b/src/lib/broadcast.jl
@@ -46,6 +46,7 @@ function Base.reducedim_init(::typeof(identity), ::typeof(accum), A::AbstractArr
 end
 
 trim(x, Δ) = reshape(Δ, ntuple(i -> size(Δ, i), Val(ndims(x))))
+trim(x::Tuple, Δ) = ntuple(k -> Δ[k], length(x))
 
 unbroadcast(x::AbstractArray, x̄) =
   size(x) == size(x̄) ? x̄ :
@@ -55,6 +56,7 @@ unbroadcast(x::AbstractArray, x̄) =
 unbroadcast(x::Number, x̄) = accum_sum(x̄)
 unbroadcast(x::Tuple{<:Any}, x̄) = (accum_sum(x̄),)
 unbroadcast(x::Base.RefValue, x̄) = (x=accum_sum(x̄),)
+unbroadcast(x::Tuple, x̄) = trim(x, length(x) == length(x̄) ? x̄ : accum_sum(x̄; dims=2:ndims(x̄))) # case length(x) > 1
 
 unbroadcast(x::AbstractArray, x̄::Nothing) = nothing
 
diff --git a/test/features.jl b/test/features.jl
index 48df0c87c..6843acbf6 100644
--- a/test/features.jl
+++ b/test/features.jl
@@ -481,3 +481,15 @@ end
   Zygote.gradient(loss_adjoint,[1.0])
   @test x[1] == x[2]
 end
+
+@testset "tuples & broadcasting" begin
+    @test gradient(x -> sum(x .+ ones(2,2)), (1,2)) == ((2,2),)
+    @test gradient(x -> sum(x .+ ones(2,2)), (1,)) == ((4,),)
+    @test gradient(x -> sum(x .+ ones(2,1)), (1,2)) == ((1,1),)
+
+    # https://github.com/FluxML/Zygote.jl/issues/975
+    gt = gradient((x,p) -> prod(x .^ p), [3,4], (1,2))
+    gv = gradient((x,p) -> prod(x .^ p), [3,4], [1,2])
+    @test gt[1] == gv[1]
+    @test collect(gt[2]) ≈ gv[2]
+end