AstaBench - End-to-End Discovery: leaderboard

Agents carry a research idea through experiment design, code, runs, analysis and a written report (E2E-Bench and its harder set), graded against task rubrics; the score is the mean of the two. Unlike paper-reproduction benchmarks the agent must design and run a new experiment, and dedicated discovery agents (Asta Panda, Asta CodeScientist) sit beside general harnesses.

Metric: Mean rubric score of E2E-Bench and E2E-Bench-Hard (0-1). Source: allenai-asta-bench-leaderboard.hf.space. Saturation forecast: Around February 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 4.7 (xHigh)0.69#79 (Claude Opus 4.7)
2Claude Sonnet 4 (20250514)0.6#387
3Claude 3.7 Sonnet (20250219)0.53#402
4Claude Sonnet 4 (20250514) (Thinking)0.35#387 (Claude Sonnet 4 (20250514))
5GPT-5 (Medium)0.33#167 (GPT-5)
6O3 (2025-04-16) (Medium)0.21#216 (O3 (2025-04-16))
7GPT-5.4 (2026-03-05) (xHigh)0.2#87 (GPT-5.4 (2026-03-05))
8GPT-4.10.12#495
9GPT-5 Mini (2025-08-07) (Medium)0.11#343 (GPT-5 Mini (2025-08-07))
10Claude 3.5 Haiku (20241022)0.03#1578
11GPT-4o (2024-08-06)0.01#740
12Gemini 2.5 Flash (Preview 05-20)0#426
13Llama 4 Scout Instruct0#1543

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=astabench-end-to-end-discovery · How It Works · Data refreshed daily, snapshot 2026-11-13.