DeepSeek-Reasonix vs SWE-agent

Side-by-side comparison of two AI agent tools

D

A reliable coding agent for complex software engineering tasks.

SWE-agentopen-source

SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

Metrics

DeepSeek-ReasonixSWE-agent
Stars35.7k20.4k
Star velocity /mo3.0k254.1176470588235
Commits (90d)5.2k6
Releases (6m)100
Overall score0.918275901387310.3816346653532465

Pros

    • +在SWE-bench基准测试中达到开源项目的最先进性能水平
    • +支持多种主流大语言模型(GPT-4o、Claude Sonnet 4等),配置灵活
    • +专为研究设计,架构简单且文档完善,易于定制和扩展

    Cons

      • -开发重心已转移到mini-swe-agent项目,原项目维护可能受到影响
      • -主要面向研究用途,生产环境的稳定性和可靠性可能不如商业解决方案

      Use Cases

        • •自动修复GitHub仓库中的代码问题和bug
        • •网络安全领域的漏洞发现和渗透测试
        • •竞赛编程和算法挑战的自动化解决

        FAQ

        Which is more popular, DeepSeek-Reasonix or SWE-agent?
        DeepSeek-Reasonix has more GitHub stars (35,721 vs 20,448).
        Which is more actively developed, DeepSeek-Reasonix or SWE-agent?
        DeepSeek-Reasonix had more commits in the last 90 days (5,247 vs 6).
        Should I use DeepSeek-Reasonix or SWE-agent?
        Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.