diff --git a/ivy/functional/frontends/torch/miscellaneous_ops.py b/ivy/functional/frontends/torch/miscellaneous_ops.py
index 98074a690de62..61624d2398762 100644
--- a/ivy/functional/frontends/torch/miscellaneous_ops.py
+++ b/ivy/functional/frontends/torch/miscellaneous_ops.py
@@ -211,6 +211,55 @@ def diag(input, diagonal=0, *, out=None):
     return ivy.diag(input, k=diagonal)
 
 
+@to_ivy_arrays_and_back
+def diag_embed(
+    input,
+    offset=0,
+    dim1=-2,
+    dim2=-1,
+):
+    def _handle_dim(rank, idx):
+        if idx >= 0 and idx < rank:
+            return idx
+        if idx < 0:
+            idx = idx + rank
+        if idx < 0 or idx >= rank:
+            raise IndexError
+        return idx
+
+    input_type = ivy.dtype(input)
+    rank = input.ndim + 1
+    dim1 = _handle_dim(rank, dim1)
+    dim2 = _handle_dim(rank, dim2)
+    if dim1 > dim2:
+        dim1, dim2 = dim2, dim1
+        offset = -offset
+    last_dim = list(input.shape)[-1]
+    if offset != 0:
+        # add padding to match the new size
+        t_shape = list(input.shape)
+        t_shape[-1] = abs(offset)
+        z = ivy.zeros(t_shape, dtype=input.dtype, device=input.device)
+        pair = (z, input) if offset > 0 else (input, z)
+        input = ivy.concat(pair, axis=-1)
+        last_dim += abs(offset)
+    input = input.expand_dims(axis=dim1).moveaxis(-1, dim2)
+    # generate ranges shifting indices based on offset
+    a_range = ivy.arange(last_dim, device=input.device, dtype=ivy.int64)
+    b_range = ivy.arange(
+        offset, last_dim + offset, device=input.device, dtype=ivy.int64
+    )
+    # broadcast
+    cond = a_range == b_range.expand_dims(axis=-1)
+    cond_shape = [last_dim if i in (dim1, dim2) else 1 for i in range(len(input.shape))]
+    cond = cond.reshape(cond_shape)
+    if input.dtype == ivy.bool:
+        ret = cond.logical_and(input)
+    else:
+        ret = ivy.where(cond, input, 0)
+    return ret.astype(input_type)
+
+
 @with_supported_dtypes(
     {"2.2 and below": ("float32", "float64", "int32", "int64")}, "torch"
 )
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
index cb1f13a438072..5c91c765d6a35 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py
@@ -424,6 +424,34 @@ def test_torch_det(
     )
 
 
+@handle_frontend_test(
+    fn_tree="torch.diag_embed",
+    dtype_and_values=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        shape=st.shared(helpers.get_shape(min_num_dims=1, max_num_dims=2), key="shape"),
+    ),
+)
+def test_torch_diag_embed(
+    *,
+    dtype_and_values,
+    test_flags,
+    on_device,
+    fn_tree,
+    frontend,
+    backend_fw,
+):
+    input_dtype, value = dtype_and_values
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        test_flags=test_flags,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        input=value[0],
+    )
+
+
 # eig
 # TODO: Test for all valid dtypes once ivy.eig supports complex data types
 @handle_frontend_test(