diff --git a/base/abstractarray.jl b/base/abstractarray.jl
index 5123aa647985f..d5d47fe855bd5 100644
--- a/base/abstractarray.jl
+++ b/base/abstractarray.jl
@@ -2153,44 +2153,6 @@ _typed_hvncat(::Type, ::Val{0}, ::AbstractArray...) = _typed_hvncat_0d_only_one(
 _typed_hvncat_0d_only_one() =
     throw(ArgumentError("a 0-dimensional array may only contain exactly one element"))
 
-function _typed_hvncat(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, xs::Number...) where {T, N}
-    all(>(0), dims) ||
-        throw(ArgumentError("`dims` argument must contain positive integers"))
-    A = Array{T, N}(undef, dims...)
-    lengtha = length(A)  # Necessary to store result because throw blocks are being deoptimized right now, which leads to excessive allocations
-    lengthx = length(xs) # Cuts from 3 allocations to 1.
-    if lengtha != lengthx
-       throw(ArgumentError("argument count does not match specified shape (expected $lengtha, got $lengthx)"))
-    end
-    hvncat_fill!(A, row_first, xs)
-    return A
-end
-
-function hvncat_fill!(A::Array, row_first::Bool, xs::Tuple)
-    # putting these in separate functions leads to unnecessary allocations
-    if row_first
-        nr, nc = size(A, 1), size(A, 2)
-        nrc = nr * nc
-        na = prod(size(A)[3:end])
-        k = 1
-        for d ∈ 1:na
-            dd = nrc * (d - 1)
-            for i ∈ 1:nr
-                Ai = dd + i
-                for j ∈ 1:nc
-                    A[Ai] = xs[k]
-                    k += 1
-                    Ai += nr
-                end
-            end
-        end
-    else
-        for k ∈ eachindex(xs)
-            A[k] = xs[k]
-        end
-    end
-end
-
 _typed_hvncat(T::Type, dim::Int, ::Bool, xs...) = _typed_hvncat(T, Val(dim), xs...) # catches from _hvncat type promoters
 
 function _typed_hvncat(::Type{T}, ::Val{N}) where {T, N}
@@ -2216,20 +2178,18 @@ function _typed_hvncat(::Type{T}, ::Val{N}, as::AbstractArray...) where {T, N}
         throw(ArgumentError("concatenation dimension must be nonnegative"))
     for a ∈ as
         ndims(a) <= N || all(x -> size(a, x) == 1, (N + 1):ndims(a)) ||
-            return _typed_hvncat(T, (ntuple(x -> 1, N - 1)..., length(as), 1), false, as...)
+            return _typed_hvncat(T, (ntuple(x -> 1, Val(N - 1))..., length(as), 1), false, as...)
             # the extra 1 is to avoid an infinite cycle
     end
 
-    nd = max(N, ndims(as[1]))
+    nd = N
 
     Ndim = 0
     for i ∈ eachindex(as)
-        a = as[i]
-        Ndim += size(a, N)
-        nd = max(nd, ndims(a))
-        for d ∈ 1:N-1
-            size(a, d) == size(as[1], d) ||
-                throw(ArgumentError("all dimensions of element $i other than $N must be of length 1"))
+        Ndim += cat_size(as[i], N)
+        nd = max(nd, cat_ndims(as[i]))
+        for d ∈ 1:N - 1
+            cat_size(as[1], d) == cat_size(as[i], d) || throw(ArgumentError("mismatched size along axis $d in element $i"))
         end
     end
 
@@ -2252,16 +2212,15 @@ function _typed_hvncat(::Type{T}, ::Val{N}, as...) where {T, N}
     nd = N
     Ndim = 0
     for i ∈ eachindex(as)
-        a = as[i]
-        Ndim += cat_size(a, N)
-        nd = max(nd, cat_ndims(a))
+        Ndim += cat_size(as[i], N)
+        nd = max(nd, cat_ndims(as[i]))
         for d ∈ 1:N-1
-            cat_size(a, d) == 1 ||
+            cat_size(as[i], d) == 1 ||
                 throw(ArgumentError("all dimensions of element $i other than $N must be of length 1"))
         end
     end
 
-    A = Array{T, nd}(undef, ntuple(x -> 1, N - 1)..., Ndim, ntuple(x -> 1, nd - N)...)
+    A = Array{T, nd}(undef, ntuple(x -> 1, Val(N - 1))..., Ndim, ntuple(x -> 1, nd - N)...)
 
     k = 1
     for a ∈ as
@@ -2277,7 +2236,6 @@ function _typed_hvncat(::Type{T}, ::Val{N}, as...) where {T, N}
     return A
 end
 
-
 # 0-dimensional cases for balanced and unbalanced hvncat method
 
 _typed_hvncat(T::Type, ::Tuple{}, ::Bool, x...) = _typed_hvncat(T, Val(0), x...)
@@ -2302,7 +2260,51 @@ function _typed_hvncat_1d(::Type{T}, ds::Int, ::Val{row_first}, as...) where {T,
     end
 end
 
-function _typed_hvncat(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, as...) where {T, N}
+function _typed_hvncat(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, xs::Number...) where {T, N}
+    all(>(0), dims) ||
+        throw(ArgumentError("`dims` argument must contain positive integers"))
+    A = Array{T, N}(undef, dims...)
+    lengtha = length(A)  # Necessary to store result because throw blocks are being deoptimized right now, which leads to excessive allocations
+    lengthx = length(xs) # Cuts from 3 allocations to 1.
+    if lengtha != lengthx
+       throw(ArgumentError("argument count does not match specified shape (expected $lengtha, got $lengthx)"))
+    end
+    hvncat_fill!(A, row_first, xs)
+    return A
+end
+
+function hvncat_fill!(A::Array, row_first::Bool, xs::Tuple)
+    # putting these in separate functions leads to unnecessary allocations
+    if row_first
+        nr, nc = size(A, 1), size(A, 2)
+        nrc = nr * nc
+        na = prod(size(A)[3:end])
+        k = 1
+        for d ∈ 1:na
+            dd = nrc * (d - 1)
+            for i ∈ 1:nr
+                Ai = dd + i
+                for j ∈ 1:nc
+                    A[Ai] = xs[k]
+                    k += 1
+                    Ai += nr
+                end
+            end
+        end
+    else
+        for k ∈ eachindex(xs)
+            A[k] = xs[k]
+        end
+    end
+end
+
+function _typed_hvncat(T::Type, dims::NTuple{N, Int}, row_first::Bool, as...) where {N}
+    # function barrier after calculating the max is necessary for high performance
+    nd = max(maximum(cat_ndims(a) for a ∈ as), N)
+    return _typed_hvncat_dims(T, (dims..., ntuple(x -> 1, nd - N)...), row_first, as)
+end
+
+function _typed_hvncat_dims(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, as::Tuple) where {T, N}
     length(as) > 0 ||
         throw(ArgumentError("must have at least one element"))
     all(>(0), dims) ||
@@ -2311,16 +2313,14 @@ function _typed_hvncat(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, as...)
     d1 = row_first ? 2 : 1
     d2 = row_first ? 1 : 2
 
-    # discover dimensions
-    nd = max(N, cat_ndims(as[1]))
-    outdims = zeros(Int, nd)
+    outdims = zeros(Int, N)
 
     # discover number of rows or columns
     for i ∈ 1:dims[d1]
         outdims[d1] += cat_size(as[i], d1)
     end
 
-    currentdims = zeros(Int, nd)
+    currentdims = zeros(Int, N)
     blockcount = 0
     elementcount = 0
     for i ∈ eachindex(as)
@@ -2328,11 +2328,11 @@ function _typed_hvncat(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, as...)
         currentdims[d1] += cat_size(as[i], d1)
         if currentdims[d1] == outdims[d1]
             currentdims[d1] = 0
-            for d ∈ (d2, 3:nd...)
+            for d ∈ (d2, 3:N...)
                 currentdims[d] += cat_size(as[i], d)
                 if outdims[d] == 0 # unfixed dimension
                     blockcount += 1
-                    if blockcount == (d > length(dims) ? 1 : dims[d]) # last expected member of dimension
+                    if blockcount == dims[d]
                         outdims[d] = currentdims[d]
                         currentdims[d] = 0
                         blockcount = 0
@@ -2375,7 +2375,13 @@ function _typed_hvncat(T::Type, shape::Tuple{Tuple}, row_first::Bool, xs...)
     return _typed_hvncat_1d(T, shape[1][1], Val(row_first), xs...)
 end
 
-function _typed_hvncat(::Type{T}, shape::NTuple{N, Tuple}, row_first::Bool, as...) where {T, N}
+function _typed_hvncat(T::Type, shape::NTuple{N, Tuple}, row_first::Bool, as...) where {N}
+    # function barrier after calculating the max is necessary for high performance
+    nd = max(maximum(cat_ndims(a) for a ∈ as), N)
+    return _typed_hvncat_shape(T, (shape..., ntuple(x -> shape[end], nd - N)...), row_first, as)
+end
+
+function _typed_hvncat_shape(::Type{T}, shape::NTuple{N, Tuple}, row_first, as::Tuple) where {T, N}
     length(as) > 0 ||
         throw(ArgumentError("must have at least one element"))
     all(>(0), tuple((shape...)...)) ||
@@ -2383,6 +2389,7 @@ function _typed_hvncat(::Type{T}, shape::NTuple{N, Tuple}, row_first::Bool, as..
 
     d1 = row_first ? 2 : 1
     d2 = row_first ? 1 : 2
+
     shapev = collect(shape) # saves allocations later
     all(!isempty, shapev) ||
         throw(ArgumentError("each level of `shape` argument must have at least one value"))
diff --git a/test/abstractarray.jl b/test/abstractarray.jl
index b43ef5e153e34..b211f471c4c2d 100644
--- a/test/abstractarray.jl
+++ b/test/abstractarray.jl
@@ -1399,6 +1399,25 @@ using Base: typed_hvncat
         @test [v v;;; fill(v, 1, 2)] == fill(v, 1, 2, 2)
     end
 
+    # output dimensions are maximum of input dimensions and concatenation dimension
+    begin
+        v1 = fill(1, 1, 1)
+        v2 = fill(1, 1, 1, 1, 1)
+        v3 = fill(1, 1, 2, 1, 1)
+        @test [v1 ;;; v2] == [1 ;;; 1 ;;;;]
+        @test [v2 ;;; v1] == [1 ;;; 1 ;;;;]
+        @test [v3 ;;; v1 v1] == [1 1 ;;; 1 1 ;;;;]
+        @test [v1 v1 ;;; v3] == [1 1 ;;; 1 1 ;;;;]
+        @test [v2 v1 ;;; v1 v1] == [1 1 ;;; 1 1 ;;;;]
+        @test [v1 v1 ;;; v1 v2] == [1 1 ;;; 1 1 ;;;;]
+        @test [v2 ;;; 1] == [1 ;;; 1 ;;;;]
+        @test [1 ;;; v2] == [1 ;;; 1 ;;;;]
+        @test [v3 ;;; 1 v1] == [1 1 ;;; 1 1 ;;;;]
+        @test [v1 1 ;;; v3] == [1 1 ;;; 1 1 ;;;;]
+        @test [v2 1 ;;; v1 v1] == [1 1 ;;; 1 1 ;;;;]
+        @test [v1 1 ;;; v1 v2] == [1 1 ;;; 1 1 ;;;;]
+    end
+
     # dims form
     for v ∈ ((), (1,), ([1],), (1, [1]), ([1], 1), ([1], [1]))
         # reject dimension < 0