Benchmarks
Benchmarks for LiteLLM Gateway (Proxy Server) tested against a fake OpenAI endpoint.
Use this config for testing:
Note: we're currently migrating to aiohttp which has 10x higher throughput. We recommend using the aiohttp_openai/
provider for load testing.
model_list:
- model_name: "fake-openai-endpoint"
litellm_params:
model: aiohttp_openai/any
api_base: https://your-fake-openai-endpoint.com/chat/completions
api_key: "test"
1 Instance LiteLLM Proxy​
Metric | Litellm Proxy (1 Instance) |
---|---|
Median Latency (ms) | 110 |
RPS | 250 |
Key Findings​
- Single instance: 250 RPS @ 100ms latency
- 4 LiteLLM instances: 1000 RPS @ 100ms latency
2 Instances​
Adding 1 instance, will double the RPS and maintain the 100ms-110ms
median latency.
Metric | Litellm Proxy (2 Instances) |
---|---|
Median Latency (ms) | 100 |
RPS | 500 |
Logging Callbacks​
GCS Bucket Logging​
Using GCS Bucket has no impact on latency, RPS compared to Basic Litellm Proxy
Metric | Basic Litellm Proxy | LiteLLM Proxy with GCS Bucket Logging |
---|---|---|
RPS | 1133.2 | 1137.3 |
Median Latency (ms) | 140 | 138 |
LangSmith logging​
Using LangSmith has no impact on latency, RPS compared to Basic Litellm Proxy
Metric | Basic Litellm Proxy | LiteLLM Proxy with LangSmith |
---|---|---|
RPS | 1133.2 | 1135 |
Median Latency (ms) | 140 | 132 |
Locust Settings​
- 2500 Users
- 100 user Ramp Up