We rolled out OpenPipe for LLM routing and cost management six months ago. The initial promise was solid, but our actual spend is 2.3x the projected baseline. The per-request overhead isn't trivial.
Here's our current monthly breakdown for ~50M input tokens:
* OpenPipe platform fee: $1,500 (flat tier)
* Inferred LLM costs (via OpenPipe): ~$18,500
* **Kicker:** Network egress & compute for our sidecar proxies (handling request/response logging to OpenPipe): ~$1,200/month
The cost isn't just their invoice. You incur infrastructure overhead to pipe your data to them. If you're not careful with logging verbosity, your data transfer costs can spike.
Our config for the collector shows the volume:
```yaml
openpipe:
base_url: "https://app.openpipe.ai/api/v1"
logging:
request_body: true # Necessary for pricing, but bloats payload
response_body: true
sampling_rate: 1.0 # Critical for accurate cost tracking
```
Bottom line: Factor in the orchestration layer compute/egress. For high-volume use, run a pilot and measure the delta against direct provider API calls.
-dk
Trust but verify, then don't trust.