OpenChainBench

OpenChainBench

OpenChainBench measures crypto infrastructure the same way for every provider, publishes the number, and ships the code that produced it. RPC endpoints, data APIs, bridges, perp DEXes, prediction markets, oracles, cross-chain messaging. Live at [openchainbench.com](https://openchainbench.com).

It answers questions like which free Ethereum RPC answers fastest, or which bridge charges least to move USDC, with figures recomputed around the clock rather than written down once.

Every benchmark ships with the harness that produces its data, under MIT, with the dataset under CC-BY-4.0, and pull requests are open to any party including the providers being measured. The card above is live, and GitHub caches it, so it can lag the page it links to.

What this is

• A public registry of benchmarks, one YAML spec per benchmark, each naming its metric, its methodology and the exact PromQL behind every figure it publishes.
• A set of self-contained Go harnesses that probe providers on a schedule and expose Prometheus metrics. One shared Prometheus scrapes them, one worker materializes snapshots, the site reads those snapshots.
• A citable data surface. Every benchmark figure is available as JSON, as Markdown, over RSS and through an MCP server. JSON responses carry an asOf timestamp, a source URL and a licence; exported citations carry the page URL and the date you retrieved it.

What this is not

• Not a token, a fund, or an RPC vendor.
• Not editable by the measured. A provider may be shown the facts behind a report before it is published, and the staging site is public, so figures are visible before a release. Nobody outside the method can change a number.
• Not a single-vendor view. Providers that cannot be measured under identical conditions are split into separate benchmarks, or filtered to the same scope, and the spec says which.

Get the data in 30 seconds

pip install openchainbench

from openchainbench import OpenChainBench

with OpenChainBench() as ocb: for b in ocb.list_benchmarks()[:5]: print(b.slug, b.leader)

head_lag = ocb.get_benchmark("aggregator-head-lag") print(head_lag.headline)

No key and no account. Read endpoints allow 60 requests a minute per IP, and the AI crawlers named in robots.txt are exempt. The same data over plain HTTP:

# every benchmark with its current value, leader and citation

curl https://openchainbench.com/api/citable

one benchmark: rankings, 24h sparkline, methodology, paste-ready quote

curl https://openchainbench.com/api/stat/aggregator-head-lag

a benchmark as Markdown instead of HTML, at the same URL

curl -H "Accept: text/markdown" https://openchainbench.com/benchmarks/bridge-fee

For an agent, point an MCP client at the hosted server:

{ "mcpServers": { "openchainbench": { "url": "https://openchainbench.com/api/mcp/mcp" } } }

It exposes list_benchmarks, get_benchmark, search_benchmarks, compare_providers, recommend_provider and list_answers, plus the openchainbench://benchmark/{slug} resource. Install notes are at /mcp.

One benchmark, end to end

A benchmark is a spec, a harness, and the surfaces generated from them. Take aggregator-head-lag, which measures how long a data API takes to emit a swap that is already on chain.

The spec (benchmarks/aggregator-head-lag.yml) declares the metric, the unit, whether higher is better, the written methodology, and one PromQL query per provider per percentile. No number on the page is typed by hand.

The harness (harnesses/aggregator-head-lag/) subscribes to chain events and to each provider's feed, races them per transaction, and exposes the result at /metrics.

The published shape, from GET /api/stat/aggregator-head-lag:

{

"slug": "aggregator-head-lag", "metric": "Head lag", "unit": "s", "higherIsBetter": false, "value": 0.240038, // example reading, 2026-10-25 "leader": { "name": "Codex", "slug": "codex", "value": 0.240038 }, // ms holds the raw series value in the benchmark's stored unit, which is // not always milliseconds: on a percent benchmark it holds a percent. "rankings": [ { "name": "Codex", "ms": { "p50": 240.038, "p90": 399.49 } } ], "sparkline": [ /* 73 points, last 24h */ ], "sampleSize": 184980, "measured": 6, "ranked": 6, "asOf": "2026-10-25T19:26:11.573Z", "freshness": { "ageHours": 0.2, "stale": false }, "headline": "...", // one sentence, ready to quote "methodology": [ /* the written rules, same text as the page */ ], "source": "https://github.com/ChainBench/OpenChainBench/tree/main/harnesses/aggregator-head-lag", "license": "CC-BY-4.0" }

headline is generated from the current reading, so it is correct whenever you fetch it and stale the moment it is pasted into a file. Quote it with its asOf. For a formal citation use /api/cite/ /bib.

By the numbers

243 specs, minus 7 held on staging, minus 2 retired benches that keep their spec, leaves 234 benchmarks that this commit publishes. Counts derived from the repository at 2026-11-06.

Published by category: RPCs 157, Trading 43, Aggregators 9, Bridges 9, Blockchains 8, RWA 6, NFT APIs 1, Wallets 1.

The badge at the top reads the live count from /api/citable, which is what production serves. The table is derived from the commit you are reading. The two agree once a change has been released, and differ while a benchmark is merged and waiting, so comparing them tells you something instead of requiring you to trust either.

Machine-readable surfaces

Every benchmark is CC-BY-4.0 and reachable without a key.

Each benchmark page also carries Dataset, StatisticalReport, Observation, TechArticle, FAQPage, DataDownload and BreadcrumbList JSON-LD.

Two mirrors are published outside this repo: a Hugging Face dataset with a daily parquet snapshot, and a Zenodo record under DOI 10.5281/zenodo.20800311.

Site surfaces

| /rpc · /perps · [/prediction-markets](https://openchainbenc