Pick merged pull requests
Each PR turns into a task that starts from the commit before the change. We keep its tests aside for grading.
NEWPrivate benchmarks from your merged PRs
Public leaderboards have never seen your code. Fullbeam builds a private benchmark from pull requests your team already merged, and grades it with your own tests. You find out what gets better, what breaks, and what it costs.
Example benchmark · Backend maintenance
GPT-6 Luna ranks #14 of 14 on a public agentic coding benchmark. On this team’s 18 merged PRs, with 3 attempts each, it passed more tasks than anything else. It was also the cheapest per accepted task of the top four.
| # | Agent · model | Public score | Pass rate on your PRs | Rank shift | Cost / accepted task |
|---|---|---|---|---|---|
| 01 | Codex ·GPT-6 LunaNew setup · backend-tools@18 | 41 #14 | 78%rank 1 on your PRs | up 13 places | €5.02 |
| 02 | Claude Code ·Opus 5.5Current setup · backend-tools@17 | 66 #1 | 72%rank 2 on your PRs | down 1 place | €8.10 |
| 03 | Codex ·GPT-6 Sol | 57 #6 | 70%rank 3 on your PRs | up 3 places | €6.40 |
| 04 | Codex ·GPT-6 Astra | 62 #2 | 68%rank 4 on your PRs | down 2 places | €7.20 |
| 05 | Claude Code ·Fable 5.1 | 62 #2 | 66%rank 5 on your PRs | down 3 places | €11.30 |
| 06 | OpenCode ·GLM-5.3 | 54 #8 | 55%rank 6 on your PRs | up 2 places | €4.60 |
Public: Artificial Analysis Coding Agent Index v1.5 rank among 14 agent/model pairs, retrieved 24 Sep 2026. Fullbeam columns are an illustrative example, not a customer result.
How it works
Trying a new model, agent, MCP tool or prompt? Compare it to what you use today in three steps.
Each PR turns into a task that starts from the commit before the change. We keep its tests aside for grading.
We write a spec for each PR and check that it doesn’t give away code, file names or tests. If it looks good, approve it in one click.
Each task runs a few times, every attempt in its own sandbox. Then a separate sandbox with no model keys runs the PR’s tests.
Tell us what you want to try and we’ll test it against your current setup. When a new model comes out, you can rerun the same tasks.
We’re in private preview and letting teams in by invite.