diff --git a/Project.toml b/Project.toml
index 6cae09c7..a3d8f23c 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "DifferentialEquations"
 uuid = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 authors = ["Chris Rackauckas <accounts@chrisrackauckas.com>"]
-version = "7.13.0"
+version = "7.14.0"
 
 [deps]
 BoundaryValueDiffEq = "764a87c0-6b3e-53db-9096-fe964310641d"
diff --git a/src/DifferentialEquations.jl b/src/DifferentialEquations.jl
index 1db63371..1ebc99e4 100644
--- a/src/DifferentialEquations.jl
+++ b/src/DifferentialEquations.jl
@@ -24,7 +24,6 @@ using NonlinearSolve
 
 include("default_solve.jl")
 include("default_arg_parsing.jl")
-include("ode_default_alg.jl")
 include("sde_default_alg.jl")
 include("dae_default_alg.jl")
 include("dde_default_alg.jl")
diff --git a/src/ode_default_alg.jl b/src/ode_default_alg.jl
deleted file mode 100644
index e701c81c..00000000
--- a/src/ode_default_alg.jl
+++ /dev/null
@@ -1,79 +0,0 @@
-function default_algorithm(prob::DiffEqBase.AbstractODEProblem{uType, tType, inplace};
-        kwargs...) where {uType, tType, inplace}
-    o = Dict{Symbol, Any}(kwargs)
-    extra_kwargs = Any[]
-    alg = AutoTsit5(Rosenbrock23(autodiff = false)) # Standard default
-    uEltype = eltype(prob.u0)
-
-    alg_hints = get_alg_hints(o)
-    tol_level = get_tolerance_level(o)
-    callbacks = callbacks_exists(o)
-    mm = mass_matrix_exists(prob)
-
-    if :stiff ∈ alg_hints && :nonstiff ∈ alg_hints
-        error("The problem must either be designated as stiff or non-stiff")
-    end
-
-    # If adaptivity is not set and the tType is not a float, turn off adaptivity
-    # Bad interaction with ForwardDiff
-    #!(tType <: AbstractFloat) && (:adaptive ∉ keys(o)) && push!(extra_kwargs,:adaptive=>false)
-
-    if prob.f isa SplitFunction
-        alg = KenCarp4(autodiff = false)
-    elseif prob.f isa DynamicalODEFunction
-        if tol_level == :low_tol || tol_level == :med_tol
-            alg = Tsit5()
-        else
-            alg = Vern7(lazy = !callbacks)
-        end
-    else # Standard ODE
-        if :nonstiff ∈ alg_hints
-            # Don't default to implicit here because of memory requirements
-            # And because the linear system gets unruly
-            if (!(uEltype <: Float64) && !(uEltype <: Float32) && !(uEltype <: Complex)) ||
-               tol_level == :extreme_tol || tol_level == :low_tol
-                # Most likely higher precision, so use a higher order method
-                alg = Vern7(lazy = !callbacks)
-            else
-                alg = Tsit5()
-            end
-        elseif :stiff ∈ alg_hints || mm # The problem is stiff
-            if length(prob.u0) > 500
-                # Use Krylov method when huge!
-                alg = FBDF(autodiff = false, linsolve = LinearSolve.KrylovJL_GMRES())
-            elseif length(prob.u0) > 50
-                alg = FBDF(autodiff = false)
-            elseif tol_level == :high_tol
-                alg = Rosenbrock23(autodiff = false)
-            else
-                alg = Rodas5P(autodiff = false)
-            end
-        else # :auto ∈ alg_hints
-            if (!(uEltype <: Float64) && !(uEltype <: Float32)) ||
-               tol_level == :extreme_tol ||
-               tol_level == :low_tol
-                # Most likely higher precision, so use a higher order method
-                if length(prob.u0) > 500
-                    alg = AutoVern7(
-                        KenCarp47(
-                            autodiff = false, linsolve = LinearSolve.KrylovJL_GMRES()),
-                        lazy = !callbacks)
-                elseif length(prob.u0) > 50
-                    alg = AutoVern7(KenCarp47(autodiff = false), lazy = !callbacks)
-                else
-                    alg = AutoVern7(Rodas5P(autodiff = false), lazy = !callbacks)
-                end
-            else # :med or low
-                if length(prob.u0) > 500
-                    alg = AutoTsit5(TRBDF2(
-                        autodiff = false, linsolve = LinearSolve.KrylovJL_GMRES()))
-                elseif length(prob.u0) > 50
-                    alg = AutoTsit5(TRBDF2(autodiff = false))
-                else
-                    alg = AutoTsit5(Rosenbrock23(autodiff = false))
-                end
-            end
-        end
-    end
-    alg, extra_kwargs
-end
diff --git a/test/default_ode_alg_test.jl b/test/default_ode_alg_test.jl
deleted file mode 100644
index e034c378..00000000
--- a/test/default_ode_alg_test.jl
+++ /dev/null
@@ -1,107 +0,0 @@
-using DifferentialEquations, Test
-
-f_2dlinear = (du, u, p, t) -> (@. du = p * u)
-f_2dlinear_analytic = (u0, p, t) -> @. u0 * exp(p * t)
-prob_ode_2Dlinear = ODEProblem(ODEFunction(f_2dlinear, analytic = f_2dlinear_analytic),
-    rand(4, 2), (0.0, 1.0), 1.01)
-
-alg, kwargs = default_algorithm(prob_ode_2Dlinear; dt = 1 // 2^(4))
-integ = init(prob_ode_2Dlinear; dt = 1 // 2^(4))
-sol = solve(prob_ode_2Dlinear; dt = 1 // 2^(4))
-
-@test sol.alg.algs[1] isa Tsit5
-@test sol.alg.algs[2] isa Rosenbrock23
-
-sol = solve(prob_ode_2Dlinear; reltol = 1e-1)
-
-@test sol.alg.algs[1] isa Tsit5
-@test sol.alg.algs[2] isa Rosenbrock23
-
-sol = solve(prob_ode_2Dlinear; reltol = 1e-7)
-
-@test sol.alg.algs[1] isa Vern7
-@test sol.alg.algs[2] isa Rodas5P
-
-sol = solve(prob_ode_2Dlinear; reltol = 1e-10)
-
-@test sol.alg.algs[1] isa Vern7
-@test sol.alg.algs[2] isa Rodas5P
-
-sol = solve(prob_ode_2Dlinear; alg_hints = [:stiff])
-
-@test sol.alg isa Rodas5P
-
-sol = solve(prob_ode_2Dlinear; alg_hints = [:stiff], reltol = 1e-1)
-
-@test sol.alg isa Rosenbrock23
-
-const linear_bigα = parse(BigFloat, "1.01")
-f = (du, u, p, t) -> begin
-    for i in 1:length(u)
-        du[i] = linear_bigα * u[i]
-    end
-end
-(::typeof(f))(::Type{Val{:analytic}}, u0, p, t) = u0 * exp(linear_bigα * t)
-prob_ode_bigfloat2Dlinear = ODEProblem(f, map(BigFloat, rand(4, 2)) .* ones(4, 2) / 2,
-    (0.0, 1.0))
-
-sol = solve(prob_ode_bigfloat2Dlinear; dt = 1 // 2^(4))
-@test sol.alg.algs[1] isa Vern7
-@test sol.alg.algs[2] isa Rodas5P
-
-default_algorithm(prob_ode_bigfloat2Dlinear; alg_hints = [:stiff])
-
-sol = solve(prob_ode_bigfloat2Dlinear; alg_hints = [:stiff])
-
-@test sol.alg isa Rodas5P
-
-sol = solve(prob_ode_bigfloat2Dlinear, nothing; alg_hints = [:stiff])
-
-@test sol.alg isa Rodas5P
-
-struct FooAlg end
-
-@test_throws DiffEqBase.NonSolverError solve(prob_ode_bigfloat2Dlinear, FooAlg();
-    default_set = true)
-
-struct FooAlg2 <: DiffEqBase.DEAlgorithm end
-
-@test_throws DiffEqBase.ProblemSolverPairingError solve(prob_ode_bigfloat2Dlinear,
-    FooAlg2(); default_set = true)
-
-prob = ODEProblem(f, rand(4, 2) .* ones(4, 2) / 2, (0.0, 1.0))
-
-sol = solve(prob; alg_hints = [:stiff])
-
-@test sol.alg isa Rodas5P
-
-sol = solve(prob; alg_hints = [:stiff], reltol = 1e-1)
-
-@test sol.alg isa Rosenbrock23
-
-sol = solve(prob; alg_hints = [:stiff], callback = CallbackSet())
-
-@test sol.alg isa Rodas5P
-
-prob = ODEProblem(f, rand(4, 2) .* ones(4, 2) / 2, (0.0, 1.0))
-
-alg, kwargs = default_algorithm(prob; alg_hints = [:stiff])
-
-@test alg isa Rodas5P
-
-m = 1.0
-ω = 1.0
-
-function mass_system!(du, u, p, t)
-    # a(t) = (1/m) w^2 x
-    (1 / m) * (ω^2) * u[1]
-end
-
-v0 = 0.0
-u0 = 1.0
-tspan = (0.0, 10.0)
-
-prob = SecondOrderODEProblem(mass_system!, v0, u0, tspan)
-sol = solve(prob)
-
-@test sol.alg isa Tsit5
diff --git a/test/runtests.jl b/test/runtests.jl
index 3953b8b1..920c9026 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -5,9 +5,6 @@ using DifferentialEquations, Test, SafeTestsets
     @time @safetestset "Default Discrete Algorithm" begin
         include("default_discrete_alg_test.jl")
     end
-    @time @safetestset "Default ODE Algorithm" begin
-        include("default_ode_alg_test.jl")
-    end
     @time @safetestset "Default Steady State Algorithm" begin
         include("default_steady_state_alg_test.jl")
     end