diff --git a/src/anndata/_io/specs/lazy_methods.py b/src/anndata/_io/specs/lazy_methods.py
index a4445c77d..6931fae0f 100644
--- a/src/anndata/_io/specs/lazy_methods.py
+++ b/src/anndata/_io/specs/lazy_methods.py
@@ -1,5 +1,8 @@
 from __future__ import annotations
 
+from contextlib import contextmanager
+from pathlib import Path
+
 import h5py
 import numpy as np
 from scipy import sparse
@@ -46,11 +49,28 @@ def make_index(is_csc, stride, shape, block_id):
     return index
 
 
+@contextmanager
+def maybe_open_h5(filename_or_elem: str | ZarrGroup, elem_name: str):
+    if isinstance(filename_or_elem, str):
+        file = h5py.File(filename_or_elem, "r")
+        try:
+            yield file[elem_name]
+        finally:
+            file.close()
+    else:
+        try:
+            yield filename_or_elem
+        finally:
+            pass
+
+
 @_LAZY_REGISTRY.register_read(H5Group, IOSpec("csc_matrix", "0.1.0"))
 @_LAZY_REGISTRY.register_read(H5Group, IOSpec("csr_matrix", "0.1.0"))
+@_LAZY_REGISTRY.register_read(ZarrGroup, IOSpec("csc_matrix", "0.1.0"))
+@_LAZY_REGISTRY.register_read(ZarrGroup, IOSpec("csr_matrix", "0.1.0"))
 def read_sparse_as_dask_h5(elem, _reader):
-    filename = elem.file.filename
-    elem_name = elem.name
+    filename_or_elem = elem.file.filename if isinstance(elem, H5Group) else elem
+    elem_name = elem.name if isinstance(elem, H5Group) else Path(elem.path).name
     shape = elem.attrs["shape"]
     dtype = elem["data"].dtype
     is_csc = elem.attrs["encoding-type"] == "csc_matrix"
@@ -58,8 +78,8 @@ def read_sparse_as_dask_h5(elem, _reader):
     def make_dask_chunk(block_id=None):
         # We need to open the file in each task since `dask` cannot share h5py objects when using `dask.distributed`
         # https://github.com/scverse/anndata/issues/1105
-        with h5py.File(filename, "r") as f:
-            mtx = ad.experimental.sparse_dataset(f[elem_name])
+        with maybe_open_h5(filename_or_elem, elem_name) as f:
+            mtx = ad.experimental.sparse_dataset(f)
             index = make_index(is_csc, stride, shape, block_id)
             chunk = mtx[index]
         return chunk
@@ -67,21 +87,6 @@ def make_dask_chunk(block_id=None):
     return make_dask_array(is_csc, shape, make_dask_chunk, dtype)
 
 
-@_LAZY_REGISTRY.register_read(ZarrGroup, IOSpec("csc_matrix", "0.1.0"))
-@_LAZY_REGISTRY.register_read(ZarrGroup, IOSpec("csr_matrix", "0.1.0"))
-def read_sparse_as_dask_zarr(elem, _reader):
-    shape = elem.attrs["shape"]
-    dtype = elem["data"].dtype
-    is_csc = elem.attrs["encoding-type"] == "csc_matrix"
-
-    def make_dask_chunk(block_id=None):
-        mtx = ad.experimental.sparse_dataset(elem)
-        index = make_index(is_csc, stride, shape, block_id)
-        return mtx[index]
-
-    return make_dask_array(is_csc, shape, make_dask_chunk, dtype)
-
-
 @_LAZY_REGISTRY.register_read(H5Array, IOSpec("array", "0.2.0"))
 def read_h5_array(elem, _reader):
     import dask.array as da