diff --git a/ext/ReactantNNlibExt.jl b/ext/ReactantNNlibExt.jl
index 5d03283ea..5b48e27b7 100644
--- a/ext/ReactantNNlibExt.jl
+++ b/ext/ReactantNNlibExt.jl
@@ -222,14 +222,20 @@ function NNlib.meanpool!(
 end
 
 NNlib.batched_transpose(x::AnyTracedRArray{T,3}) where {T} = permutedims(x, (2, 1, 3))
-NNlib.batched_adjoint(x::AnyTracedRArray{<:Real,3}) = NNlib.batched_transpose(x)
+function NNlib.batched_adjoint(x::AnyTracedRArray{T,3}) where {T}
+    y = permutedims(x, (2, 1, 3))
+    conj!(y)
+    return y
+end
 
-function NNlib.batched_mul(x::AnyTracedRArray{T,3}, y::AnyTracedRArray{T,3}) where {T}
+function NNlib.batched_mul!(
+    res::TracedRArray{T1,3}, x::AnyTracedRArray{T2,3}, y::AnyTracedRArray{T3,3}
+) where {T1,T2,T3}
     if (size(x, 3) != size(y, 3) && size(x, 3) != 1 && size(y, 3) != 1) ||
         (size(x, 2) != size(y, 1))
         throw(
             DimensionMismatch(
-                lazy"size(x) = $(size(x)), size(y) = $(size(y)) inconsistent for batched_matmul.",
+                lazy"size(x) = $(size(x)), size(y) = $(size(y)) inconsistent for batched_mul.",
             ),
         )
     end
@@ -238,7 +244,7 @@ function NNlib.batched_mul(x::AnyTracedRArray{T,3}, y::AnyTracedRArray{T,3}) whe
 
     B = max(size(x, 1), size(y, 1))
     out_shape = (B, size(x, 2), size(y, 3))
-    resty = MLIR.IR.TensorType(out_shape, eltype(MLIR.IR.type(x.mlir_data)))
+    resty = MLIR.IR.TensorType(out_shape, eltype(MLIR.IR.type(res.mlir_data)))
 
     if size(x, 1) != size(y, 1)
         if size(x, 1) == 1
@@ -255,7 +261,7 @@ function NNlib.batched_mul(x::AnyTracedRArray{T,3}, y::AnyTracedRArray{T,3}) whe
     prec = MLIR.IR.Attribute(
         MLIR.API.stablehloPrecisionAttrGet(MLIR.IR.context(), "DEFAULT")
     )
-    res = TracedRArray{T,3}(
+    tmp = TracedRArray{T1,3}(
         (),
         MLIR.IR.result(
             MLIR.Dialects.stablehlo.dot_general(
@@ -269,7 +275,8 @@ function NNlib.batched_mul(x::AnyTracedRArray{T,3}, y::AnyTracedRArray{T,3}) whe
         ),
         size(resty),
     )
-    return permutedims(res, (2, 3, 1))
+    res.mlir_data = permutedims(tmp, (2, 3, 1)).mlir_data
+    return res
 end
 
 function NNlib.pad_constant(