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secapi.ai vs SEC-API.io: A Head-to-Head Benchmark Comparison

We ran structured, reproducible benchmarks across four core SEC-data workflows: entity resolution, filing search, XBRL fact retrieval, and insider trade queries. Every test used the same inputs, the same machine, and the same measurement methodology. Here are the results.

4 workflow benchmarks
Reproducible methodology
Dated capture: 2026-03-18
p50 and p95 latency

Methodology

How we measured

Each benchmark claim is scoped to the workload, capture date, provider inputs, metric definition, checked-in artifact, and caveat block. We measure latency percentiles, decoded response payload bytes, and response-shape usefulness for the workflows agents repeat. Full methodology and raw data are published in the docs.

Results

Head-to-head results

These results render from the shared dated benchmark model instead of duplicated marketing copy.

latency

Entity resolve p50 latency

Resolve a public issuer by ticker or identifier with canonical metadata and provenance.

ProviderValueNotes
SEC API33.98 ms
sec-api.io231.46 ms
Captured 2026-03-18. Canonical benchmark harness against identical issuer and filing workflows. The competitor latency and payload measurements (sec-api.io, financialdatasets.ai) were captured 2026-03-18; the scorecard summary was last regenerated 2026-06-10 from those captured artifacts.

latency

Filing search p50 latency

Search recent SEC filings with agent-ready metadata and a compact response contract.

ProviderValueNotes
SEC API37.62 ms
sec-api.io265.23 ms
Captured 2026-03-18. Canonical benchmark harness against identical issuer and filing workflows. The competitor latency and payload measurements (sec-api.io, financialdatasets.ai) were captured 2026-03-18; the scorecard summary was last regenerated 2026-06-10 from those captured artifacts.

latency

Structured facts p50 latency

Return normalized financial facts instead of a giant filing payload.

ProviderValueNotes
SEC API34.45 ms
sec-api.io400.53 ms
Captured 2026-03-18. Canonical benchmark harness against identical issuer and filing workflows. The competitor latency and payload measurements (sec-api.io, financialdatasets.ai) were captured 2026-03-18; the scorecard summary was last regenerated 2026-06-10 from those captured artifacts.

payload

Structured facts payload size

Average bytes returned for the structured-facts workflow in the dated benchmark suite.

ProviderValueNotes
SEC API1,522 bytes
sec-api.io1,426,498 bytes
Captured 2026-03-18. Canonical benchmark harness against identical issuer and filing workflows. The competitor latency and payload measurements (sec-api.io, financialdatasets.ai) were captured 2026-03-18; the scorecard summary was last regenerated 2026-06-10 from those captured artifacts.

Payload efficiency

Smaller payloads mean faster agent workflows

Payload claims should use the structured benchmark rows above instead of duplicated percentages. For agent workflows that make hundreds of calls per session, smaller decoded response bytes compound into meaningful token savings and faster end-to-end completion times. Default SEC data responses include freshness timestamps and provenance metadata, while compact and agent views keep the citation fields needed for auditability.

  • Use the dated payload-size card when making exact token-efficiency claims.
  • Use compact response modes for agent defaults.
  • Keep provenance, freshness, and request tracing fields in compact views.
  • Avoid raw percentage claims unless the percentage is generated from the checked-in artifact.

Caveats

What these benchmarks do and do not show

These benchmarks measure specific workflows on specific dates. Performance varies by endpoint, query complexity, and server load. We publish the methodology so you can reproduce the tests. We do not claim universal superiority -- we claim measurable wins on the workflows that agent-heavy SEC data consumers repeat most often.

See for yourself

Run your own benchmarks against any alternative, using the published methodology.