diff --git a/fiftyone/core/models.py b/fiftyone/core/models.py
index f6f557ed1bf..0f88ddd9d3d 100644
--- a/fiftyone/core/models.py
+++ b/fiftyone/core/models.py
@@ -75,6 +75,7 @@ def apply_model(
     store_logits=False,
     batch_size=None,
     num_workers=None,
+    num_writer_workers=None,
     skip_failures=True,
     output_dir=None,
     rel_dir=None,
@@ -105,6 +106,8 @@ def apply_model(
             batching
         num_workers (None): the number of workers to use when loading images.
             Only applicable for Torch-based models
+        num_writer_workers (None): the number of thread workers to use when
+            writing predictions. Only applicable for Torch-based models.
         skip_failures (True): whether to gracefully continue without raising an
             error if predictions cannot be generated for a sample. Only
             applicable to :class:`Model` instances
@@ -284,6 +287,7 @@ def apply_model(
                 filename_maker,
                 progress,
                 field_mapping,
+                num_writer_workers,
             )
 
         if batch_size is not None:
@@ -457,6 +461,7 @@ def _apply_image_model_data_loader(
     filename_maker,
     progress,
     field_mapping,
+    num_writer_workers,
 ):
     needs_samples = isinstance(model, SamplesMixin)
 
@@ -480,7 +485,7 @@ def _apply_image_model_data_loader(
         ctx = context.enter_context(foc.SaveContext(samples))
         submit = context.enter_context(
             fou.async_executor(
-                max_workers=1,
+                max_workers=num_writer_workers,
                 skip_failures=skip_failures,
                 warning="Async failure labeling batches",
             )
@@ -904,6 +909,7 @@ def compute_embeddings(
     embeddings_field=None,
     batch_size=None,
     num_workers=None,
+    num_writer_workers=None,
     skip_failures=True,
     progress=None,
     **kwargs,
@@ -934,6 +940,8 @@ def compute_embeddings(
             batching
         num_workers (None): the number of workers to use when loading images.
             Only applicable for Torch-based models
+        num_writer_workers (None): the number of thread workers to use when
+            writing embeddings. Only applicable for Torch-based models.
         skip_failures (True): whether to gracefully continue without raising an
             error if embeddings cannot be generated for a sample. Only
             applicable to :class:`Model` instances
@@ -1078,6 +1086,7 @@ def compute_embeddings(
                 skip_failures,
                 progress,
                 field_mapping,
+                num_writer_workers,
             )
 
         if batch_size is not None:
@@ -1200,6 +1209,7 @@ def _compute_image_embeddings_data_loader(
     skip_failures,
     progress,
     field_mapping,
+    num_writer_workers,
 ):
     data_loader = _make_data_loader(
         samples,
@@ -1224,7 +1234,7 @@ def _compute_image_embeddings_data_loader(
 
         submit = context.enter_context(
             fou.async_executor(
-                max_workers=1,
+                max_workers=num_writer_workers,
                 skip_failures=skip_failures,
                 warning="Async failure saving embeddings",
             )
diff --git a/fiftyone/core/utils.py b/fiftyone/core/utils.py
index c3fb2d841a1..d6a48b9027e 100644
--- a/fiftyone/core/utils.py
+++ b/fiftyone/core/utils.py
@@ -2859,14 +2859,19 @@ def recommend_thread_pool_workers(num_workers=None):
     If a ``fo.config.max_thread_pool_workers`` is set, this limit is applied.
 
     Args:
-        num_workers (None): a suggested number of workers
+        num_workers (None): a suggested number of workers. If ``num_workers <= 0``, this
+            function returns 1.
 
     Returns:
         a number of workers
     """
+
     if num_workers is None:
         num_workers = multiprocessing.cpu_count()
 
+    if num_workers <= 0:
+        num_workers = 1
+
     if fo.config.max_thread_pool_workers is not None:
         num_workers = min(num_workers, fo.config.max_thread_pool_workers)
 
@@ -3147,7 +3152,7 @@ def validate_hex_color(value):
 
 @contextmanager
 def async_executor(
-    *, max_workers, skip_failures=False, warning="Async failure"
+    *, max_workers=None, skip_failures=False, warning="Async failure"
 ):
     """
     Context manager that provides a function for submitting tasks to a thread
@@ -3160,7 +3165,8 @@ def async_executor(
                 submit(process_item, item)
 
     Args:
-        max_workers: the maximum number of workers to use
+        max_workers (None): the maximum number of workers to use. By default,
+            this is determined by :func:`fiftyone.core.utils.recommend_thread_pool_workers`.
         skip_failures (False): whether to skip exceptions raised by tasks
         warning ("Async failure"): the warning message to log if a task
             raises an exception and ``skip_failures == True``
@@ -3168,6 +3174,12 @@ def async_executor(
     Raises:
         Exception: if a task raises an exception and ``skip_failures == False``
     """
+    if max_workers is None:
+        max_workers = (
+            fo.config.default_thread_pool_workers
+            or recommend_thread_pool_workers(max_workers)
+        )
+
     with ThreadPoolExecutor(max_workers=max_workers) as executor:
         _futures = []