diff --git a/jax/experimental/array_api/__init__.py b/jax/experimental/array_api/__init__.py
index c0b7a28e79ae..ed936be4e98c 100644
--- a/jax/experimental/array_api/__init__.py
+++ b/jax/experimental/array_api/__init__.py
@@ -85,6 +85,7 @@
     expand_dims as expand_dims,
     expm1 as expm1,
     eye as eye,
+    finfo as finfo,
     flip as flip,
     float32 as float32,
     float64 as float64,
@@ -193,7 +194,6 @@
 
 from jax.experimental.array_api._data_type_functions import (
     astype as astype,
-    finfo as finfo,
 )
 
 from jax.experimental.array_api._elementwise_functions import (
diff --git a/jax/experimental/array_api/_data_type_functions.py b/jax/experimental/array_api/_data_type_functions.py
index 248c1c6dd0fe..3ff95befc6fe 100644
--- a/jax/experimental/array_api/_data_type_functions.py
+++ b/jax/experimental/array_api/_data_type_functions.py
@@ -14,34 +14,15 @@
 
 from __future__ import annotations
 
-import builtins
-from typing import NamedTuple
-import numpy as np
-
 import jax.numpy as jnp
 
 from jax._src.lib import xla_client as xc
 from jax._src.sharding import Sharding
 from jax._src import dtypes as _dtypes
 
-# TODO(micky774): Update jax.numpy dtypes to dtype *objects*
-bool = np.dtype('bool')
-int8 = np.dtype('int8')
-int16 = np.dtype('int16')
-int32 = np.dtype('int32')
-int64 = np.dtype('int64')
-uint8 = np.dtype('uint8')
-uint16 = np.dtype('uint16')
-uint32 = np.dtype('uint32')
-uint64 = np.dtype('uint64')
-float32 = np.dtype('float32')
-float64 = np.dtype('float64')
-complex64 = np.dtype('complex64')
-complex128 = np.dtype('complex128')
-
 
 # TODO(micky774): Remove when jax.numpy.astype is deprecation is completed
-def astype(x, dtype, /, *, copy: builtins.bool = True, device: xc.Device | Sharding | None = None):
+def astype(x, dtype, /, *, copy: bool = True, device: xc.Device | Sharding | None = None):
   src_dtype = x.dtype if hasattr(x, "dtype") else _dtypes.dtype(x)
   if (
     src_dtype is not None
@@ -54,25 +35,3 @@ def astype(x, dtype, /, *, copy: builtins.bool = True, device: xc.Device | Shard
       "your input."
     )
   return jnp.astype(x, dtype, copy=copy, device=device)
-
-
-class FInfo(NamedTuple):
-    bits: int
-    eps: float
-    max: float
-    min: float
-    smallest_normal: float
-    dtype: jnp.dtype
-
-# TODO(micky774): Update jax.numpy.finfo so that its attributes are python
-# floats
-def finfo(type, /) -> FInfo:
-  info = jnp.finfo(type)
-  return FInfo(
-    bits=info.bits,
-    eps=float(info.eps),
-    max=float(info.max),
-    min=float(info.min),
-    smallest_normal=float(info.smallest_normal),
-    dtype=jnp.dtype(type)
-  )
diff --git a/jax/experimental/array_api/skips.txt b/jax/experimental/array_api/skips.txt
index c865fabcfb55..f7d80d94f96f 100644
--- a/jax/experimental/array_api/skips.txt
+++ b/jax/experimental/array_api/skips.txt
@@ -1,5 +1,8 @@
 # Known failures for the array api tests.
 
+# finfo return type misalignment (https://github.com/data-apis/array-api/issues/405)
+array_api_tests/test_data_type_functions.py::test_finfo[float32]
+
 # Test suite attempts in-place mutation:
 array_api_tests/test_special_cases.py::test_iop
 array_api_tests/test_special_cases.py::test_nan_propagation