diff --git a/docs/my-website/docs/load_test.md b/docs/my-website/docs/load_test.md
index bd97c62290b..c1fac60fcb2 100644
--- a/docs/my-website/docs/load_test.md
+++ b/docs/my-website/docs/load_test.md
@@ -213,7 +213,191 @@ asyncio.run(loadtest_fn())
 
 ```
 
-## Multi-Instance TPM/RPM Load Test
+## Multi-Instance TPM/RPM Load Test (Router)
+
+Test if your defined tpm/rpm limits are respected across multiple instances of the Router object. 
+
+In our test:
+- Max RPM per deployment is = 100 requests per minute
+- Max Throughput / min on router = 200 requests per minute (2 deployments)
+- Load we'll send through router = 600 requests per minute
+
+:::info
+
+If you don't want to call a real LLM API endpoint, you can setup a fake openai server. [See code](#extra---setup-fake-openai-server)
+
+:::
+
+### 1. Setup Router 
+
+```python
+from litellm import Router 
+import litellm
+litellm.suppress_debug_info = True
+litellm.set_verbose = False
+import logging
+logging.basicConfig(level=logging.CRITICAL)
+import os, random, uuid, time, asyncio
+
+os.environ["REDIS_SSL"] = "True"
+
+# Model list for OpenAI and Anthropic models
+model_list = [
+    {
+        "model_name": "fake-openai-endpoint",
+        "litellm_params": {
+            "model": "gpt-3.5-turbo",
+            "api_key": "my-fake-key",
+            "api_base": "http://0.0.0.0:8080",
+            "rpm": 100
+        },
+    },
+    {
+        "model_name": "fake-openai-endpoint",
+        "litellm_params": {
+            "model": "gpt-3.5-turbo",
+            "api_key": "my-fake-key",
+            "api_base": "http://0.0.0.0:8081",
+            "rpm": 100
+        },
+    },
+]
+
+router_1 = Router(model_list=model_list, num_retries=0, enable_pre_call_checks=True, redis_host=os.getenv("REDIS_HOST"), redis_port=os.getenv("REDIS_PORT"), redis_password=os.getenv("REDIS_PASSWORD"))
+router_2 = Router(model_list=model_list, num_retries=0, enable_pre_call_checks=True, redis_host=os.getenv("REDIS_HOST"), redis_port=os.getenv("REDIS_PORT"), redis_password=os.getenv("REDIS_PASSWORD"))
+
+
+
+async def router_completion_non_streaming():
+  try:
+    client: Router = random.sample([router_1, router_2], 1)[0] # randomly pick b/w clients
+    # print(f"client={client}")
+    response = await client.acompletion(
+              model="fake-openai-endpoint", # [CHANGE THIS] (if you call it something else on your proxy)
+              messages=[{"role": "user", "content": f"This is a test: {uuid.uuid4()}"}],
+          )
+    return response
+  except Exception as e:
+    # print(e)
+    return None
+  
+async def loadtest_fn():
+    start = time.time()
+    n = 500  # Number of concurrent tasks
+    tasks = [router_completion_non_streaming() for _ in range(n)]
+    chat_completions = await asyncio.gather(*tasks)
+    successful_completions = [c for c in chat_completions if c is not None]
+    print(n, time.time() - start, len(successful_completions))
+
+def get_utc_datetime():
+    import datetime as dt
+    from datetime import datetime
+
+    if hasattr(dt, "UTC"):
+        return datetime.now(dt.UTC)  # type: ignore
+    else:
+        return datetime.utcnow()  # type: ignore
+
+
+# Run the event loop to execute the async function
+async def parent_fn():
+  for _ in range(10):
+    dt = get_utc_datetime()
+    current_minute = dt.strftime("%H-%M")
+    print(f"triggered new batch - {current_minute}")
+    await loadtest_fn()
+    await asyncio.sleep(10)
+
+asyncio.run(parent_fn())
+
+```
+
+### 2. Test it! 
+
+Let's hit the router with 600 requests per minute. 
+
+Copy this script 👇. Save it as `test_loadtest_router.py` AND run it with `python3 test_loadtest_router.py`
+
+
+```python
+from litellm import Router 
+import litellm
+litellm.suppress_debug_info = True
+litellm.set_verbose = False
+import logging
+logging.basicConfig(level=logging.CRITICAL)
+import os, random, uuid, time, asyncio
+
+# Model list for OpenAI and Anthropic models
+model_list = [
+    {
+        "model_name": "fake-openai-endpoint",
+        "litellm_params": {
+            "model": "gpt-3.5-turbo",
+            "api_key": "my-fake-key",
+            "api_base": "http://0.0.0.0:8080",
+            "rpm": 100
+        },
+    },
+    {
+        "model_name": "fake-openai-endpoint",
+        "litellm_params": {
+            "model": "gpt-3.5-turbo",
+            "api_key": "my-fake-key",
+            "api_base": "http://0.0.0.0:8081",
+            "rpm": 100
+        },
+    },
+]
+
+router_1 = Router(model_list=model_list, num_retries=0, enable_pre_call_checks=True, redis_host=os.getenv("REDIS_HOST"), redis_port=os.getenv("REDIS_PORT"), redis_password=os.getenv("REDIS_PASSWORD"))
+router_2 = Router(model_list=model_list, num_retries=0, enable_pre_call_checks=True, redis_host=os.getenv("REDIS_HOST"), redis_port=os.getenv("REDIS_PORT"), redis_password=os.getenv("REDIS_PASSWORD"))
+
+
+
+async def router_completion_non_streaming():
+  try:
+    client: Router = random.sample([router_1, router_2], 1)[0] # randomly pick b/w clients
+    # print(f"client={client}")
+    response = await client.acompletion(
+              model="fake-openai-endpoint", # [CHANGE THIS] (if you call it something else on your proxy)
+              messages=[{"role": "user", "content": f"This is a test: {uuid.uuid4()}"}],
+          )
+    return response
+  except Exception as e:
+    # print(e)
+    return None
+  
+async def loadtest_fn():
+    start = time.time()
+    n = 600  # Number of concurrent tasks
+    tasks = [router_completion_non_streaming() for _ in range(n)]
+    chat_completions = await asyncio.gather(*tasks)
+    successful_completions = [c for c in chat_completions if c is not None]
+    print(n, time.time() - start, len(successful_completions))
+
+def get_utc_datetime():
+    import datetime as dt
+    from datetime import datetime
+
+    if hasattr(dt, "UTC"):
+        return datetime.now(dt.UTC)  # type: ignore
+    else:
+        return datetime.utcnow()  # type: ignore
+
+
+# Run the event loop to execute the async function
+async def parent_fn():
+  for _ in range(10):
+    dt = get_utc_datetime()
+    current_minute = dt.strftime("%H-%M")
+    print(f"triggered new batch - {current_minute}")
+    await loadtest_fn()
+    await asyncio.sleep(10)
+
+asyncio.run(parent_fn())
+```
+## Multi-Instance TPM/RPM Load Test (Proxy)
 
 Test if your defined tpm/rpm limits are respected across multiple instances. 
 
@@ -277,6 +461,8 @@ litellm --config /path/to/config.yaml --port 4001
 
 Let's hit the proxy with 600 requests per minute. 
 
+Copy this script 👇. Save it as `test_loadtest_proxy.py` AND run it with `python3 test_loadtest_proxy.py`
+
 ```python
 from openai import AsyncOpenAI, AsyncAzureOpenAI
 import random, uuid
@@ -308,7 +494,7 @@ async def proxy_completion_non_streaming():
   
 async def loadtest_fn():
     start = time.time()
-    n = 500  # Number of concurrent tasks
+    n = 600  # Number of concurrent tasks
     tasks = [proxy_completion_non_streaming() for _ in range(n)]
     chat_completions = await asyncio.gather(*tasks)
     successful_completions = [c for c in chat_completions if c is not None]