diff --git a/metaworld/__init__.py b/metaworld/__init__.py
index 5e3a499cb..a3255ebe0 100644
--- a/metaworld/__init__.py
+++ b/metaworld/__init__.py
@@ -490,8 +490,8 @@ def _make_ml_envs_inner(
 
 def make_ml_envs(
     name: str,
-    seed: int,
-    meta_batch_size: int,
+    seed: int | None = None,
+    meta_batch_size: int = 20,
     total_tasks_per_cls: int | None = None,
     max_episode_steps: int | None = None,
     split: Literal["train", "test"] = "train",
@@ -533,6 +533,44 @@ def make_ml_envs(
 
 
 def register_mw_envs() -> None:
+    def _mt_bench_vector_entry_point(
+        mt_bench: str,
+        vector_strategy: Literal["sync", "async"],
+        seed=None,
+        use_one_hot=False,
+        num_envs=None,
+        *args,
+        **lamb_kwargs,
+    ):
+        return make_mt_envs(  # type: ignore
+            mt_bench,
+            seed=seed,
+            use_one_hot=use_one_hot,
+            vector_strategy=vector_strategy,  # type: ignore
+            *args,
+            **lamb_kwargs,
+        )
+
+    def _ml_bench_vector_entry_point(
+        ml_bench: str,
+        split: str,
+        vector_strategy: Literal["sync", "async"],
+        seed: int | None = None,
+        meta_batch_size: int = 20,
+        num_envs=None,
+        *args,
+        **lamb_kwargs,
+    ):
+        env_generator = make_ml_envs_train if split == "train" else make_ml_envs_test
+        return env_generator(
+            ml_bench,
+            seed=seed,
+            meta_batch_size=meta_batch_size,
+            vector_strategy=vector_strategy,
+            *args,
+            **lamb_kwargs,
+        )
+
     for name in ALL_V3_ENVIRONMENTS.keys():
         kwargs = {"name": name}
         register(
@@ -540,16 +578,15 @@ def register_mw_envs() -> None:
             entry_point="metaworld:make_mt_envs",
             kwargs=kwargs,
         )
-        register(
-            id=f"Meta-World/ML1-train-{name}",
-            entry_point="metaworld:make_ml_envs_train",
-            kwargs=kwargs,
-        )
-        register(
-            id=f"Meta-World/ML1-test-{name}",
-            entry_point="metaworld:make_ml_envs_test",
-            kwargs=kwargs,
-        )
+        for vector_strategy in ["sync", "async"]:
+            for split in ["train", "test"]:
+                register(
+                    id=f"Meta-World/ML1-{split}-{name}-{vector_strategy}",
+                    vector_entry_point=partial(
+                        _ml_bench_vector_entry_point, name, split, vector_strategy
+                    ),
+                    kwargs={},
+                )
 
     for name_hid in ALL_V3_ENVIRONMENTS_GOAL_HIDDEN:
         register(
@@ -571,25 +608,6 @@ def register_mw_envs() -> None:
 
     for mt_bench in ["MT10", "MT50"]:
         for vector_strategy in ["sync", "async"]:
-
-            def _mt_bench_vector_entry_point(
-                mt_bench: str,
-                vector_strategy: str,
-                seed=None,
-                use_one_hot=False,
-                num_envs=None,
-                *args,
-                **lamb_kwargs,
-            ):
-                return make_mt_envs(  # type: ignore
-                    mt_bench,
-                    seed=seed,
-                    use_one_hot=use_one_hot,
-                    vector_strategy=vector_strategy,  # type: ignore
-                    *args,
-                    **lamb_kwargs,
-                )
-
             register(
                 id=f"Meta-World/{mt_bench}-{vector_strategy}",
                 vector_entry_point=partial(
@@ -601,33 +619,10 @@ def _mt_bench_vector_entry_point(
     for ml_bench in ["ML10", "ML45"]:
         for vector_strategy in ["sync", "async"]:
             for split in ["train", "test"]:
-
-                def _ml_bench_vector_entry_point(
-                    split: str,
-                    ml_bench: str,
-                    vector_strategy: str,
-                    seed=None,
-                    meta_batch_size: int = 20,
-                    num_envs=None,
-                    *args,
-                    **lamb_kwargs,
-                ):
-                    env_generator = (
-                        make_ml_envs_train if split == "train" else make_ml_envs_test
-                    )
-                    return env_generator(
-                        ml_bench,
-                        seed=seed,
-                        meta_batch_size=meta_batch_size,
-                        vector_strategy=vector_strategy,
-                        *args,
-                        **lamb_kwargs,
-                    )
-
                 register(
                     id=f"Meta-World/{ml_bench}-{split}-{vector_strategy}",
                     vector_entry_point=partial(
-                        _ml_bench_vector_entry_point, split, ml_bench, vector_strategy
+                        _ml_bench_vector_entry_point, ml_bench, split, vector_strategy
                     ),
                 )