diff --git a/src/gauss_adjoint.jl b/src/gauss_adjoint.jl
index 2c176d85f..953c82f53 100644
--- a/src/gauss_adjoint.jl
+++ b/src/gauss_adjoint.jl
@@ -480,8 +480,18 @@ function vec_pjac!(out, λ, y, t, S::GaussIntegrand)
         ReverseDiff.reverse_pass!(tape)
         copyto!(vec(out), ReverseDiff.deriv(tp))
     elseif sensealg.autojacvec isa ZygoteVJP
-        _dy, back = Zygote.pullback(tunables) do tunables
-            vec(f(y, repack(tunables), t))
+        if SciMLBase.isinplace(sol.prob.f)
+            # For in-place functions, create an out-of-place wrapper using Zygote.Buffer
+            # to allow mutation during the forward pass while remaining differentiable
+            _dy, back = Zygote.pullback(tunables) do tunables
+                du_buf = Zygote.Buffer(y)
+                f(du_buf, y, repack(tunables), t)
+                vec(copy(du_buf))
+            end
+        else
+            _dy, back = Zygote.pullback(tunables) do tunables
+                vec(f(y, repack(tunables), t))
+            end
         end
         tmp = back(λ)
         if tmp[1] === nothing
diff --git a/test/gauss_zygote_inplace.jl b/test/gauss_zygote_inplace.jl
new file mode 100644
index 000000000..fb750a2ef
--- /dev/null
+++ b/test/gauss_zygote_inplace.jl
@@ -0,0 +1,73 @@
+using SciMLSensitivity, DifferentialEquations, Zygote
+using Test
+
+# Test for issue #1282: GaussAdjoint with ZygoteVJP should handle in-place ODE functions
+@testset "GaussAdjoint with ZygoteVJP and in-place ODE" begin
+    function fiip(du, u, p, t)
+        du[1] = p[1] * u[1] - p[2] * u[1] * u[2]
+        du[2] = -p[3] * u[2] + p[4] * u[1] * u[2]
+        return nothing
+    end
+
+    p = [1.5, 1.0, 3.0, 1.0]
+    u0 = [1.0; 1.0]
+    prob = ODEProblem{true, SciMLBase.FullSpecialize}(
+        ODEFunction{true, SciMLBase.FullSpecialize}(fiip),
+        u0, (0.0, 10.0), p
+    )
+
+    # Test that basic solve works
+    sol = solve(prob, KenCarp4(), sensealg = GaussAdjoint())
+    @test sol.retcode == ReturnCode.Success
+
+    # Test that gradient computation with ZygoteVJP works
+    loss(u0,
+        p) = sum(solve(
+        prob, KenCarp4(), u0 = u0, p = p, saveat = 0.1,
+        sensealg = GaussAdjoint(autojacvec = ZygoteVJP())
+    ))
+
+    # This should not throw MethodError anymore
+    du0, dp = Zygote.gradient(loss, u0, p)
+
+    @test du0 !== nothing
+    @test dp !== nothing
+    @test length(du0) == 2
+    @test length(dp) == 4
+
+    # Test with explicit ZygoteVJP specification
+    (dp2,) = Zygote.gradient(p) do p
+        sum(solve(prob, KenCarp4(), p = p, saveat = 0.1,
+            sensealg = GaussAdjoint(autojacvec = ZygoteVJP())))
+    end
+
+    @test dp2 !== nothing
+    @test length(dp2) == 4
+end
+
+# Test out-of-place still works
+@testset "GaussAdjoint with ZygoteVJP and out-of-place ODE" begin
+    function foop(u, p, t)
+        dx = p[1] * u[1] - p[2] * u[1] * u[2]
+        dy = -p[3] * u[2] + p[4] * u[1] * u[2]
+        [dx, dy]
+    end
+
+    p = [1.5, 1.0, 3.0, 1.0]
+    u0 = [1.0; 1.0]
+    prob = ODEProblem(foop, u0, (0.0, 10.0), p)
+
+    # Test that gradient computation with ZygoteVJP works for out-of-place
+    loss(u0,
+        p) = sum(solve(
+        prob, Tsit5(), u0 = u0, p = p, saveat = 0.1,
+        sensealg = GaussAdjoint(autojacvec = ZygoteVJP())
+    ))
+
+    du0, dp = Zygote.gradient(loss, u0, p)
+
+    @test du0 !== nothing
+    @test dp !== nothing
+    @test length(du0) == 2
+    @test length(dp) == 4
+end