--- title: "AutoAgent vs SWE-agent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hkuds-autoagent-vs-swe-agent-swe-agent" tools: ["hkuds-autoagent", "swe-agent-swe-agent"] --- # AutoAgent vs SWE-agent *GraphCanon updated Aug 19, 2026* ## Verdict Pick AutoAgent if autoAgent is a framework designed for creating automated AI agents using large language models in a zero-code, fully-automated environment. It operates with Python and uses Docker to manage agent-interaction environments; pick SWE-agent if critical Facts for SWE-agent. [AutoAgent](https://arxiv.org/abs/2502.05957) reports 9.7k GitHub stars, 1.4k forks, and 68 open issues, last pushed Oct 16, 2025. [SWE-agent](https://swe-agent.com) has 20k stars, 2.2k forks, and 82 open issues, last pushed Aug 17, 2026. Figures are from public GitHub metadata via [AutoAgent's repository](https://github.com/HKUDS/AutoAgent) and [SWE-agent's repository](https://github.com/SWE-agent/SWE-agent). | | [AutoAgent](/tools/hkuds-autoagent.md) | [SWE-agent](/tools/swe-agent-swe-agent.md) | | --- | --- | --- | | Tagline | Fully-Automated and Zero-Code LLM Agent Framework | Automatically fixes GitHub issues using a chosen language model | | Stars | 9,738 | 20,079 | | Forks | 1,357 | 2,201 | | Open issues | 68 | 82 | | Language | Python | Python | | Adopt for | AutoAgent is a framework designed for creating automated AI agents using large language models in a zero-code, fully-automated environment. It operates with Python and uses Docker to manage agent-interaction environments | Critical Facts for SWE-agent | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AutoAgent](/tools/hkuds-autoagent.md) | [SWE-agent](/tools/swe-agent-swe-agent.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 307d | 1d | | Open issues (now) | 68 | 82 | | Stars delta | +242 (30d) | +227 (30d) | | Open issues delta | -1 (30d) | +39 (30d) | | Full report | [trust report](/tools/hkuds-autoagent/trust.md) | [trust report](/tools/swe-agent-swe-agent/trust.md) | ## Decision facts: AutoAgent - **Adopt for:** AutoAgent is a framework designed for creating automated AI agents using large language models in a zero-code, fully-automated environment. It operates with Python and uses Docker to manage agent-interaction environments ## Decision facts: SWE-agent - **Adopt for:** Critical Facts for SWE-agent ## Choose when ### Choose AutoAgent if… - Tags unique to AutoAgent: llms. - Use AutoAgent when you aim to leverage LLMs in an automation setting without needing any coding experience. - Leaner open-issue backlog (68). ### Choose SWE-agent if… - Tags unique to SWE-agent: agent-based-model, ai, cybersecurity, llm. - Also covers Developer Tools. - You need to automatically fix GitHub issues using a selected language model and want the flexibility of defining which model powers the agent's responses. ## When NOT to use AutoAgent - Avoid AutoAgent if your project requires customization or modification of the underlying agent framework code directly. - Do not use AutoAgent when you require real-time performance and low latency operation since its automatic Docker image handling can cause delays in deployment. ## When NOT to use SWE-agent - If you prefer using a single fixed model for all issues without the option to select different language models based on the task's requirements. - For projects that require deep domain-specific knowledge beyond general coding tasks or where human judgment plays an essential role. - In scenarios where security standards are extremely stringent and automated systems, especially those that leverage external data for training like LLMs, may not meet compliance requirements. ## Common questions ### What is the difference between AutoAgent and SWE-agent? AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework. SWE-agent: Automatically fixes GitHub issues using a chosen language model. See the comparison table for live GitHub stats and shared categories. ### When should I choose AutoAgent over SWE-agent? Choose AutoAgent over SWE-agent when Tags unique to AutoAgent: llms; Use AutoAgent when you aim to leverage LLMs in an automation setting without needing any coding experience; Leaner open-issue backlog (68). ### When should I choose SWE-agent over AutoAgent? Choose SWE-agent over AutoAgent when Tags unique to SWE-agent: agent-based-model, ai, cybersecurity, llm; Also covers Developer Tools; You need to automatically fix GitHub issues using a selected language model and want the flexibility of defining which model powers the agent's responses. ### When should I avoid AutoAgent? Avoid AutoAgent if your project requires customization or modification of the underlying agent framework code directly. Do not use AutoAgent when you require real-time performance and low latency operation since its automatic Docker image handling can cause delays in deployment. ### When should I avoid SWE-agent? If you prefer using a single fixed model for all issues without the option to select different language models based on the task's requirements. For projects that require deep domain-specific knowledge beyond general coding tasks or where human judgment plays an essential role. In scenarios where security standards are extremely stringent and automated systems, especially those that leverage external data for training like LLMs, may not meet compliance requirements. ### Is AutoAgent or SWE-agent more popular on GitHub? SWE-agent has more GitHub stars (20,079 vs 9,738). Stars measure visibility, not whether either tool fits your constraints. ### Are AutoAgent and SWE-agent open source? Yes - both are open-source projects on GitHub (AutoAgent: MIT, SWE-agent: MIT). ### Where can I find alternatives to AutoAgent or SWE-agent? GraphCanon lists graph-backed alternatives at [AutoAgent alternatives](/tools/hkuds-autoagent/alternatives) and [SWE-agent alternatives](/tools/swe-agent-swe-agent/alternatives) ([AutoAgent markdown twin](/tools/hkuds-autoagent/alternatives.md), [SWE-agent markdown twin](/tools/swe-agent-swe-agent/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/hkuds-autoagent-vs-swe-agent-swe-agent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AutoAgent or SWE-agent? AutoAgent: Slowing. SWE-agent: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for AutoAgent and SWE-agent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoAgent trust report](/tools/hkuds-autoagent/trust); [SWE-agent trust report](/tools/swe-agent-swe-agent/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hkuds-autoagent`](/api/graphcanon/graph?tool=hkuds-autoagent) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_