diff --git a/bioimageio_colab/register_sam_service.py b/bioimageio_colab/register_sam_service.py
index d699607..ee8ab9a 100644
--- a/bioimageio_colab/register_sam_service.py
+++ b/bioimageio_colab/register_sam_service.py
@@ -181,6 +181,19 @@ def segment(
 
     return features
 
+def compute_embedding(model_cache: TTLCache, model_name, image, context=None):
+    user_id = context["user"].get("id")
+    sam_predictor = _load_model(model_cache, model_name, user_id)
+    logger.info(
+        f"User {user_id} - Computing image embedding (model: '{model_name}')..."
+    )
+    sam_predictor.set_image(_to_image(image))
+    return {
+        "model_name": model_name,
+        "original_size": sam_predictor.original_size,
+        "input_size": sam_predictor.input_size,
+        "features": sam_predictor.get_image_embedding().cpu().numpy(),
+    }
 
 def clear_cache(embedding_cache: TTLCache, context: dict = None) -> bool:
     user_id = context["user"].get("id")
@@ -239,6 +252,13 @@ async def register_service(args: dict) -> None:
             # Returns:
             # - a list of XY coordinates of the segmented polygon in the format (1, N, 2)
             "segment": partial(segment, model_cache, embedding_cache),
+            # **Compute the embedding of an image**
+            # Params:
+            # - model name
+            # - image to compute the embeddings on
+            # Returns:
+            # - a dictionary containing the computed embedding, original size, and input size
+            "compute_embedding": partial(compute_embedding, model_cache),
             # **Clear the embedding cache**
             # Returns:
             # - True if the embedding was removed successfully
diff --git a/pyproject.toml b/pyproject.toml
index 7fb3208..5bc71ca 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,7 +3,7 @@ requires = ["setuptools", "wheel"]
 
 [project]
 name = "bioimageio-colab"
-version = "0.1.3"
+version = "0.1.4"
 readme = "README.md"
 description = "Collaborative image annotation and model training with human in the loop."
 dependencies = [
diff --git a/test/test_model_service.py b/test/test_model_service.py
index ee3fc15..be49ecf 100644
--- a/test/test_model_service.py
+++ b/test/test_model_service.py
@@ -6,6 +6,7 @@
 SERVER_URL = "https://hypha.aicell.io"
 WORKSPACE_NAME = "bioimageio-colab"
 SERVICE_ID = "microsam"
+MODEL_NAME = "vit_b"
 
 
 def test_service_available():
@@ -24,6 +25,19 @@ def test_get_service():
     assert segment_svc.get("segment")
     assert segment_svc.get("clear_cache")
 
-    features = segment_svc.segment(model_name="vit_b", image=np.random.rand(256, 256), point_coordinates=[[128, 128]], point_labels=[1])
+    # Test segmentation
+    image = np.random.rand(256, 256)
+    features = segment_svc.segment(model_name=MODEL_NAME, image=image, point_coordinates=[[128, 128]], point_labels=[1])
     assert features
+
+    # Test embedding caching
+    features = segment_svc.segment(model_name=MODEL_NAME, image=image, point_coordinates=[[20, 50]], point_labels=[1])
+    features = segment_svc.segment(model_name=MODEL_NAME, image=image, point_coordinates=[[180, 10]], point_labels=[1])
+
+    # Test embedding computation for running SAM client-side
+    result = segment_svc.compute_embedding(model_name=MODEL_NAME, image=image)
+    assert result
+    embedding = result["features"]
+    assert embedding.shape == (1, 256, 64, 64)
+
     assert segment_svc.clear_cache()