diff --git a/test/components/embedders/test_hugging_face_api_document_embedder.py b/test/components/embedders/test_hugging_face_api_document_embedder.py
index 1fdde5c5c..93e49a0d4 100644
--- a/test/components/embedders/test_hugging_face_api_document_embedder.py
+++ b/test/components/embedders/test_hugging_face_api_document_embedder.py
@@ -4,6 +4,7 @@
 
 import os
 import random
+import sys
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -376,7 +377,8 @@ class TestHuggingFaceAPIDocumentEmbedder:
         not os.environ.get("HF_API_TOKEN", None),
         reason="Export an env var called HF_API_TOKEN containing the Hugging Face token to run this test.",
     )
-    @pytest.mark.flaky(reruns=2, reruns_delay=10)
+    @pytest.mark.flaky(reruns=3, reruns_delay=10)
+    @pytest.mark.skipif(sys.platform != "linux", reason="We only test on Linux to avoid overloading the HF server")
     def test_live_run_serverless(self):
         docs = [
             Document(content="I love cheese", meta={"topic": "Cuisine"}),
@@ -389,6 +391,7 @@ class TestHuggingFaceAPIDocumentEmbedder:
             meta_fields_to_embed=["topic"],
             embedding_separator=" | ",
         )
+        embedder._client.timeout = 10  # we want to fail fast if the server is not responding
         result = embedder.run(documents=docs)
         documents_with_embeddings = result["documents"]
 
diff --git a/test/components/embedders/test_hugging_face_api_text_embedder.py b/test/components/embedders/test_hugging_face_api_text_embedder.py
index 80f641c23..1ca599b15 100644
--- a/test/components/embedders/test_hugging_face_api_text_embedder.py
+++ b/test/components/embedders/test_hugging_face_api_text_embedder.py
@@ -4,6 +4,7 @@
 
 import os
 import random
+import sys
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -216,16 +217,18 @@ class TestHuggingFaceAPITextEmbedder:
 
     @pytest.mark.integration
     @pytest.mark.slow
-    @pytest.mark.flaky(reruns=2, reruns_delay=10)
+    @pytest.mark.flaky(reruns=3, reruns_delay=10)
     @pytest.mark.skipif(
         not os.environ.get("HF_API_TOKEN", None),
         reason="Export an env var called HF_API_TOKEN containing the Hugging Face token to run this test.",
     )
+    @pytest.mark.skipif(sys.platform != "linux", reason="We only test on Linux to avoid overloading the HF server")
     def test_live_run_serverless(self):
         embedder = HuggingFaceAPITextEmbedder(
             api_type=HFEmbeddingAPIType.SERVERLESS_INFERENCE_API,
             api_params={"model": "sentence-transformers/all-MiniLM-L6-v2"},
         )
+        embedder._client.timeout = 10  # we want to fail fast if the server is not responding
         result = embedder.run(text="The food was delicious")
 
         assert len(result["embedding"]) == 384
@@ -234,14 +237,16 @@ class TestHuggingFaceAPITextEmbedder:
     @pytest.mark.integration
     @pytest.mark.asyncio
     @pytest.mark.slow
-    @pytest.mark.flaky(reruns=2, reruns_delay=10)
+    @pytest.mark.flaky(reruns=3, reruns_delay=10)
     @pytest.mark.skipif(os.environ.get("HF_API_TOKEN", "") == "", reason="HF_API_TOKEN is not set")
+    @pytest.mark.skipif(sys.platform != "linux", reason="We only test on Linux to avoid overloading the HF server")
     async def test_live_run_async_serverless(self):
         model_name = "sentence-transformers/all-MiniLM-L6-v2"
 
         embedder = HuggingFaceAPITextEmbedder(
             api_type=HFEmbeddingAPIType.SERVERLESS_INFERENCE_API, api_params={"model": model_name}
         )
+        embedder._client.timeout = 10  # we want to fail fast if the server is not responding
 
         text = "This is a test sentence for embedding."
         result = await embedder.run_async(text=text)