MLOps-Bench - Base ReAct - Test Pass: leaderboard

MLOps-Bench (2026), practical ML engineering tasks in reproducible environments; Base ReAct harness, published evaluation split with separate development tasks. Task completion requires every task test to pass; test pass averages partial correctness. The three agent harnesses are separate boards; effort and API snapshots not supplied by the paper are not inferred. Rate (%); higher is better.

Metric: Rate (%). Source: arxiv.org. Saturation forecast: Around August 2027. 3 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.547.9#31
2Claude Sonnet 4.639.2#90
3GPT-5.231.4#110

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=mlops-bench-base-react-test-pass · How It Works · Data refreshed daily, snapshot 2026-10-20.