diff --git a/tests/congruence_tests/test_rate_limit.py b/tests/congruence_tests/test_rate_limit.py
new file mode 100644
index 000000000..7e20d46b4
--- /dev/null
+++ b/tests/congruence_tests/test_rate_limit.py
@@ -0,0 +1,242 @@
+from time import sleep
+
+import numpy as np
+import pytest
+
+from qdrant_client.common.client_exceptions import ResourceQuotaExceeded, ResourceExhaustedResponse
+from qdrant_client.http import models
+from tests.congruence_tests.test_common import (
+    COLLECTION_NAME,
+    compare_collections,
+    generate_fixtures,
+    init_remote,
+)
+
+
+UPLOAD_NUM_VECTORS = 100
+WRITE_LIMIT = 3
+READ_LIMIT = 2
+
+
+def test_upsert_hits_large_request_limit(remote_client):
+    grpc_client = init_remote(prefer_grpc=True)
+    points = generate_fixtures(UPLOAD_NUM_VECTORS)
+    ids, payload = [], []
+    vectors = {}
+    for point in points:
+        ids.append(point.id)
+        payload.append(point.payload)
+        for vector_name, vector in point.vector.items():
+            if vector_name not in vectors:
+                vectors[vector_name] = []
+            vectors[vector_name].append(vector)
+
+    points_batch = models.Batch(
+        ids=ids,
+        vectors=vectors,
+        payloads=payload,
+    )
+
+    remote_client.update_collection(
+        collection_name=COLLECTION_NAME,
+        strict_mode_config=models.StrictModeConfig(
+            enabled=True, read_rate_limit=READ_LIMIT, write_rate_limit=WRITE_LIMIT
+        ),
+    )
+
+    with pytest.raises(
+        ResourceQuotaExceeded,
+        match="Write rate limit exceeded, request larger than than rate limiter capacity, please try to split your request",
+    ):
+        remote_client.upsert(COLLECTION_NAME, points_batch)
+
+    with pytest.raises(
+        ResourceQuotaExceeded,
+        match="Write rate limit exceeded, request larger than than rate limiter capacity, please try to split your request",
+    ):
+        grpc_client.upsert(COLLECTION_NAME, points_batch)
+
+
+def test_upsert_hits_write_rate_limit(remote_client):
+    grpc_client = init_remote(prefer_grpc=True)
+    points = generate_fixtures(WRITE_LIMIT)
+    ids, payload = [], []
+    vectors = {}
+    for point in points:
+        ids.append(point.id)
+        payload.append(point.payload)
+        for vector_name, vector in point.vector.items():
+            if vector_name not in vectors:
+                vectors[vector_name] = []
+            vectors[vector_name].append(vector)
+
+    points_batch = models.Batch(
+        ids=ids,
+        vectors=vectors,
+        payloads=payload,
+    )
+
+    remote_client.update_collection(
+        collection_name=COLLECTION_NAME,
+        strict_mode_config=models.StrictModeConfig(
+            enabled=True, read_rate_limit=READ_LIMIT, write_rate_limit=WRITE_LIMIT
+        ),
+    )
+
+    flag = False
+    time_to_sleep = 0
+    try:
+        for _ in range(10):
+            remote_client.upsert(COLLECTION_NAME, points_batch)
+    except ResourceExhaustedResponse as ex:
+        print(ex.message)
+        assert ex.retry_after_s > 0, f"Unexpected retry_after_s value: {ex.retry_after_s}"
+        flag = True
+        time_to_sleep = int(ex.retry_after_s)
+
+    if flag:
+        # verify next response after sleep succeeds
+        sleep(time_to_sleep)
+        remote_client.upsert(COLLECTION_NAME, points_batch)
+    else:
+        raise AssertionError(
+            "No ResourceExhaustedResponse exception was raised for remote_client."
+        )
+
+    flag = False
+    try:
+        for _ in range(10):
+            grpc_client.upsert(COLLECTION_NAME, points_batch)
+    except ResourceExhaustedResponse as ex:
+        print(f"{ex.message}")
+        assert ex.retry_after_s > 0, f"Unexpected retry_after_s value: {ex.retry_after_s}"
+        flag = True
+
+    if flag:
+        # verify next response after sleep succeeds
+        sleep(time_to_sleep)
+        grpc_client.upsert(COLLECTION_NAME, points_batch)
+    else:
+        raise AssertionError("No ResourceExhaustedResponse exception was raised for grpc_client.")
+
+
+def test_upload_collection_succeeds_with_limits(local_client, remote_client):
+    grpc_client = init_remote(prefer_grpc=True)
+
+    points = generate_fixtures(10)
+
+    vectors = []
+    payload = []
+    ids = []
+    for point in points:
+        (ids.append(point.id),)
+        vectors.append(point.vector)
+        payload.append(point.payload)
+
+    remote_client.update_collection(
+        collection_name=COLLECTION_NAME,
+        strict_mode_config=models.StrictModeConfig(
+            enabled=True, read_rate_limit=READ_LIMIT, write_rate_limit=WRITE_LIMIT
+        ),
+    )
+
+    local_client.upload_collection(COLLECTION_NAME, vectors, payload, ids=ids)
+    remote_client.upload_collection(
+        COLLECTION_NAME, vectors, payload, ids=ids, wait=True, max_retries=1
+    )
+    grpc_client.upload_collection(
+        COLLECTION_NAME, vectors, payload, ids=ids, wait=True, max_retries=1
+    )
+
+    compare_collections(local_client, remote_client, UPLOAD_NUM_VECTORS)
+    compare_collections(local_client, grpc_client, UPLOAD_NUM_VECTORS)
+
+
+def test_upload_points_succeeds_with_limits(local_client, remote_client):
+    grpc_client = init_remote(prefer_grpc=True)
+    points = generate_fixtures(10)
+
+    remote_client.update_collection(
+        collection_name=COLLECTION_NAME,
+        strict_mode_config=models.StrictModeConfig(
+            enabled=True, read_rate_limit=READ_LIMIT, write_rate_limit=WRITE_LIMIT
+        ),
+    )
+
+    local_client.upload_points(COLLECTION_NAME, points)
+    remote_client.upload_points(COLLECTION_NAME, points, wait=True, max_retries=1)
+    grpc_client.upload_points(COLLECTION_NAME, points, wait=True, max_retries=1)
+
+    compare_collections(local_client, remote_client, UPLOAD_NUM_VECTORS)
+    compare_collections(local_client, grpc_client, UPLOAD_NUM_VECTORS)
+
+
+def test_query_hits_read_rate_limit(remote_client):
+    grpc_client = init_remote(prefer_grpc=True)
+
+    dense_vector_query_batch_text = []
+    for _ in range(READ_LIMIT):
+        dense_vector_query_batch_text.append(
+            models.QueryRequest(
+                query=np.random.random(50).tolist(),
+                prefetch=models.Prefetch(
+                    query=np.random.random(50).tolist(), limit=5, using="text"
+                ),
+                limit=5,
+                using="text",
+                with_payload=True,
+            )
+        )
+
+    remote_client.update_collection(
+        collection_name=COLLECTION_NAME,
+        strict_mode_config=models.StrictModeConfig(
+            enabled=True, read_rate_limit=READ_LIMIT, write_rate_limit=WRITE_LIMIT
+        ),
+    )
+
+    flag = False
+    time_to_sleep = 0
+    try:
+        for _ in range(10):
+            remote_client.query_batch_points(
+                collection_name=COLLECTION_NAME, requests=dense_vector_query_batch_text
+            )
+    except ResourceExhaustedResponse as ex:
+        print(ex.message)
+        assert ex.retry_after_s > 0, f"Unexpected retry_after_s value: {ex.retry_after_s}"
+        flag = True
+        time_to_sleep = int(ex.retry_after_s)
+
+    if flag:
+        # verify next response after sleep succeeds
+        sleep(time_to_sleep)
+        remote_client.query_batch_points(
+            collection_name=COLLECTION_NAME, requests=dense_vector_query_batch_text
+        )
+    else:
+        raise AssertionError(
+            "No ResourceExhaustedResponse exception was raised for remote_client."
+        )
+
+    flag = False
+    time_to_sleep = 0
+    try:
+        for _ in range(10):
+            grpc_client.query_batch_points(
+                collection_name=COLLECTION_NAME, requests=dense_vector_query_batch_text
+            )
+    except ResourceExhaustedResponse as ex:
+        print(ex.message)
+        assert ex.retry_after_s > 0, f"Unexpected retry_after_s value: {ex.retry_after_s}"
+        flag = True
+        time_to_sleep = int(ex.retry_after_s)
+
+    if flag:
+        # verify next response after sleep succeeds
+        sleep(time_to_sleep)
+        grpc_client.query_batch_points(
+            collection_name=COLLECTION_NAME, requests=dense_vector_query_batch_text
+        )
+    else:
+        raise AssertionError("No ResourceExhaustedResponse exception was raised for grpc_client.")