diff --git a/src/Ops.jl b/src/Ops.jl
index 8a2c15798..01a7105cd 100644
--- a/src/Ops.jl
+++ b/src/Ops.jl
@@ -1557,4 +1557,90 @@ use [`MLIR.Dialects.stablehlo.dynamic_slice`](@ref) instead.
     )
 end
 
+# XXX: kwargs
+# XXX: some of the args are not batched
+# XXX: Arbitrary dimensions for batching
+# XXX: Out-axis
+# XXX: Multiple arg return
+function batch(f, args::Vector{<:TracedRArray})
+    batch_sizes = [size(x, 1) for x in args]
+    @assert allequal(batch_sizes) "batching dimensions must be equal"
+    B = first(batch_sizes)
+
+    in_tys = [
+        MLIR.IR.TensorType(size(arg)[2:end], MLIR.IR.Type(Reactant.unwrapped_eltype(arg)))
+        for arg in args
+    ]
+
+    sym_visibility = MLIR.IR.Attribute("private")
+
+    mod = MLIR.IR.mmodule()
+    func = MLIR.IR.block!(MLIR.IR.body(mod)) do
+        return MLIR.Dialects.func.func_(;
+            sym_name=string(f) * "_batch_tmp",
+            function_type=MLIR.IR.FunctionType(in_tys, []),
+            body=MLIR.IR.Region(),
+            sym_visibility,
+        )
+    end
+    fnbody = MLIR.IR.Block(in_tys, [MLIR.IR.Location() for arg in args])
+    push!(MLIR.IR.region(func, 1), fnbody)
+
+    linear_args = [
+        TracedRArray{Reactant.unwrapped_eltype(arg),ndims(arg) - 1}(
+            (), nothing, size(arg)[2:end]
+        ) for arg in args
+    ]
+
+    MLIR.IR.activate!(fnbody)
+    result = try
+        for (i, arg) in enumerate(linear_args)
+            raw_arg = MLIR.IR.argument(fnbody, i)
+            Reactant.TracedUtils.set_mlir_data!(arg, raw_arg)
+        end
+        # XXX: call_with_reactant is not working here?
+        # ERROR: type Nothing has no field stmts
+        # res = Reactant.call_with_reactant(f, linear_args...)
+        res = f(linear_args...)
+        @assert res isa TracedRArray
+        MLIR.Dialects.func.return_([res.mlir_data])
+        res
+    finally
+        MLIR.IR.deactivate!(fnbody)
+    end
+
+    comp_func = MLIR.IR.block!(MLIR.IR.body(mod)) do
+        return MLIR.Dialects.func.func_(;
+            sym_name=string(f) * "_batch",
+            function_type=MLIR.IR.FunctionType(in_tys, [mlir_type(result)]),
+            body=MLIR.IR.Region(),
+            sym_visibility,
+        )
+    end
+    MLIR.API.mlirRegionTakeBody(MLIR.IR.region(comp_func, 1), MLIR.IR.region(func, 1))
+    MLIR.API.mlirOperationDestroy(func.operation)
+    func.operation = MLIR.API.MlirOperation(C_NULL)
+
+    fname = Reactant.TracedUtils.get_attribute_by_name(comp_func, "sym_name")
+    fname = MLIR.IR.FlatSymbolRefAttribute(Base.String(fname))
+
+    batch_inputs = [x.mlir_data for x in args]
+    output_shape = (B, size(result)...)
+    out_tys = [
+        MLIR.IR.TensorType(output_shape, MLIR.IR.Type(Reactant.unwrapped_eltype(result)))
+    ]
+
+    res = MLIR.Dialects.enzyme.batch(
+        batch_inputs;
+        outputs=out_tys,
+        fn=fname,
+        batch_shape=MLIR.IR.DenseArrayAttribute(Int64[B]),
+    )
+
+    res = MLIR.IR.result(res, 1)
+    return TracedRArray{Reactant.unwrapped_eltype(result),ndims(result) + 1}(
+        (), res, output_shape
+    )
+end
+
 end # module Ops