DeepSWE is an open-source coding agent developed by Together AI and Agentica, designed to enhance software engineering tasks through advanced artificial intelligence. Built upon Alibaba’s Qwen3-32B model, DeepSWE utilizes reinforcement learning (RL) to autonomously improve its coding capabilities, setting a new standard in AI-driven software development tools.
Key Features
- Reinforcement Learning Training: Unlike traditional supervised learning methods, DeepSWE is trained exclusively using RL, enabling it to adapt and improve through continuous interaction with real-world software engineering tasks.
- High Benchmark Performance: DeepSWE achieves a 59% accuracy on the SWE-Bench-Verified benchmark, surpassing previous open-weight models. It also boasts a 42.2% Pass@1 rate, indicating a strong ability to solve problems correctly on the first attempt.
- Open-Source Transparency: The project is fully open-sourced, with Together AI and Agentica providing access to the model weights, training framework, and evaluation logs. This openness promotes reproducibility and invites collaboration from the developer and research communities.
Who Is It For?
DeepSWE is tailored for software engineers, developers, and organizations seeking to integrate AI into their coding workflows. Its advanced capabilities can assist in automating complex coding tasks, debugging, and feature implementation, thereby enhancing productivity and code quality.
Final Thoughts
DeepSWE represents a significant advancement in AI-driven software engineering tools. Its innovative use of reinforcement learning, coupled with impressive benchmark performance and a commitment to open-source principles, makes it a valuable resource for professionals aiming to leverage AI in their development processes. By providing transparency and fostering community collaboration, DeepSWE sets a new benchmark for the future of coding agents.
Visit together.ai/blog/deepswe for more.
