FrogNano: Training a 4B Coding Agent via Online Task Synthesis
We present FrogNano, a 4B coding agent designed to tackle software engineering (SWE) tasks efficiently and effectively, even under resource-constrained environments. It is post-trained exclusively via RL on around 1,500 SWE environments with synthetic tasks. A key ingredient for improving performance is an online task synthesis pipeline that creates tasks calibrated to the frontier of learnability for the current checkpoint. This report provides evidence that competitive small coding agents can be trained with synthetic tasks alone, without traditional distillation from larger models, and that generating tasks at the learnability frontier of the current agent is important. We report detai...
| Authors | Minseon Kim, Zhengyan Shi, Emiliano Penaloza et al. |
|---|---|
| Primary category | cs.AI |
| Published | 7 September 2026 |
| Last updated at source | 5 October 2026 |
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