Methodology
This is a first-party head-to-head benchmark run by our own canonical harness, not a third-party study. Our production workflow uses GitHub Actionsubuntu-latest. Within each workflow run, comparands execute sequentially on the same runner, which GitHub assigns from a variable pool.
- Competitor measurements captured 2026-03-18; re-run before citing as current
- Hosted APIs tested from the same GitHub Actions runner within a workflow run
- Each operation run 5+ times with p50, p95, p99 latency reported
- Payload size measured as response body bytes
- Token estimate = ceil(payload_bytes / 4)
- All tests use authenticated API keys on production endpoints
- Reproduction scripts available in our benchmark methodology notes
Results
Latency Comparison
Overall: 18 wins, 0 losses, 2 ties across our benchmark suite.
Token Efficiency
How To Interpret Token Efficiency
When AI agents query SEC data, every byte of the API response consumes tokens. Smaller responses mean:- Lower cost — fewer tokens = lower API bills
- Faster reasoning — less context for the model to process
- More room — more data fits in the context window
Pricing Comparison
For light agent usage (200 queries/month):
- sec-api.io: $49/month (minimum tier)
- SEC API PAYG: $4.00/month (92% savings)
What SEC API Offers That sec-api.io Doesn’t
- Semantic search — AI-powered filing search using finance-tuned embeddings + vector search
- Intelligence bundles — Pre-computed company, security, and earnings briefings
- MCP integration — Native agent protocol support for Claude, Cursor, and other AI tools
- CLI tool —
npm install -g @secapi/clifor terminal workflows - Filing diff — Compare two filing versions to see what changed
- Saved monitors — Webhook alerts when new filings match your criteria
- Budget controls — Spending caps with 75/90/95% threshold alerts
- 4 SDKs — JavaScript, Python, Go, and Rust (sec-api.io has 2)
- 8 pre-built skills — Installable workflows for Claude Code, Codex, Cowork

