ScarfBench (Kaggle) - Deploy: leaderboard

Coding agents (one model at one effort inside its harness, run by Kaggle) carry out 204 migrations of enterprise Java applications between Jakarta EE, Quarkus and Spring; the score is the share of the 204 migrations whose application builds and deploys, the gate before any smoke test runs. Unlike the ScarfBench paper board (174 focused-app migrations, one skills prompt), Kaggle runs and maintains these results over focused and whole applications.

Metric: Migrations that build and deploy (%) of 204 Java framework migrations, each model run in a coding-agent harness by Kaggle. Source: www.kaggle.com. Saturation forecast: Estimated already saturated. 11 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 4 Argon (High)97.55#11 (Gemini 4 Argon)
2Claude Opus 5 (xHigh)97.55#22 (Claude Opus 5)
3Gemini 3.8 Flash (Medium)97.06#36 (Gemini 3.8 Flash)
4Kimi K3 (Max)96.08#54 (Kimi K3)
5GPT-6 Astra (High)96.08#6 (GPT-6 Astra)
6GPT-6.1 Sol (Max)95.59#10 (GPT-6.1 Sol)
7Claude Opus 5.5 (Max)95.1#5 (Claude Opus 5.5)
8DeepSeek V4.1 Flash (Max)94.61#59 (DeepSeek V4.1 Flash)
9Qwen 3.8 Max (xHigh)94.12#55 (Qwen 3.8 Max)
10Gemini 3.1 Pro (Preview) (High)83.33#94 (Gemini 3.1 Pro (Preview))

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

Interactive version: theaggregate.ai/benchmark?slug=scarfbench-kaggle-deploy · How It Works · Data refreshed daily, snapshot 2026-11-13.