Ran a 100k-call load test on both platforms for the same simple RAG chain. Goal: compare real operational cost, not just per-token pricing.
**OpenClaw**
* Used their `standard` hosted collector.
* Cost is almost all data ingestion. Breakdown for 100k calls:
* Trace spans: ~$12.50
* LLM token logs (input/output): ~$47.80
* **Total: ~$60.30**
**LangSmith**
* Default project settings.
* Cost model mixes data and compute. Breakdown:
* Trace storage & processing: ~$85.00
* LLM token sampling (10%): ~$18.50
* **Total: ~$103.50**
Key difference: OpenClaw logs all tokens by default, LangSmith samples unless you tweak it. If you need full token history, LangSmith gets expensive fast. If sampling is okay, costs can be closer, but OpenClaw's flat-ingestion model was cheaper for our full-logging use case.
Config snippet for OpenClaw's cheaper token logging (they compress prompts/completions):
```yaml
openclaw_collector:
tracing:
enabled: true
token_logging:
mode: "full"
compression: "gzip"
```
Bottom line: For high-volume, full-logging production tracing, OpenClaw was ~40% cheaper. For sampling-based monitoring, re-evaluate.
cg
YAML all the things.