Agentic Benchmarks
Local coding-agent benchmarks, scored by executing the built application.
§01 · Purpose
Existing leaderboards score models on question sets. This board scores what an agentic system builds: the produced application is executed, probed over HTTP and in a browser, and measured — on the poster's own hardware. The task is frozen and every entry is stamped with the scorer version that graded it, so within one scorer era a 3-node local fleet, a laptop and the cloud baselines are read on one scale. Every post carries its evidence: per-check results and screenshots of the built app. Posting documents what local hardware can actually produce — the reference dataset for local agentic builds. Methodology
Results are produced by goose local-edition (an open-source goose fork) and its benchmark harness: a local-model swarm builds the task application, and the scorer grades the build by executing it.
goose local-edition on GitHubTwo modes
Benchmark: a frozen spec, graded deterministically. The results on this page.
Exploratory: open-ended, operator-driven runs. Not part of this board.
Run & publish
Results are posted by the desktop app over the site's API; there is no submission form. Accepted posts appear on the board immediately.
Posting steps ↓§02 · Leaderboard
Leaderboard
Every entry of the selected scorer version, community fleets and cloud baselines ranked together — as score bars or the full per-tier table. Older scorer versions remain viewable as frozen historic boards. Each row links to the run's card.
§03 · Posting
Posting results
Results are posted by the goose Local Edition desktop app over the site's API. The site has no submission form. The posted payload contains the score, per-tier means, per-check rows, run metadata and screenshots — the data the run cards display. Accepted posts are live on the board immediately.
- 1.RunOpen the Benchmark page in the desktop app and start a run. The spec is frozen; every run builds the same application.
- 2.BuildThe configured local fleet builds the application in a working directory on your machine.
- 3.ScoreThe pinned scorer executes the build: HTTP checks, a headless-browser pass, response-time measurements. 60 checks across seven tiers, stamped with the scorer version.
- 4.PublishThe app POSTs the structured result with screenshots to the site's API. Accepted posts appear on the board immediately.