--- title: "koog vs AutoGPT" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jetbrains-koog-vs-significant-gravitas-autogpt" tools: ["jetbrains-koog", "significant-gravitas-autogpt"] --- # koog vs AutoGPT *GraphCanon updated Jul 15, 2026* ## Verdict Pick koog when koog is primarily Kotlin; AutoGPT is Python; pick AutoGPT when autoGPT is primarily Python; koog is Kotlin. [koog](https://docs.koog.ai) reports 4.4k GitHub stars, 447 forks, and 162 open issues, last pushed Jul 6, 2026. [AutoGPT](https://agpt.co) has 185k stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [koog's repository](https://github.com/JetBrains/koog) and [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT). | | [koog](/tools/jetbrains-koog.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Tagline | Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-brow | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | | Stars | 4,447 | 185,464 | | Forks | 447 | 46,111 | | Open issues | 162 | 494 | | Language | Kotlin | Python | | Adopt for | - | AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | AI Agents, Inference & Serving, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [koog](/tools/jetbrains-koog.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 9d | 0d | | Open issues (now) | 162 | 494 | | Full report | [trust report](/tools/jetbrains-koog/trust.md) | [trust report](/tools/significant-gravitas-autogpt/trust.md) | ## Decision facts: AutoGPT - **Adopt for:** AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. ## Choose when ### Choose koog if… - koog is primarily Kotlin; AutoGPT is Python. - License: koog is Apache-2.0, AutoGPT is Other. - Tags unique to koog: agentframework, ai-agents-framework, aiagentframework, android-ai. - Also covers Inference & Serving. ### Choose AutoGPT if… - AutoGPT is primarily Python; koog is Kotlin. - License: AutoGPT is Other, koog is Apache-2.0. - Tags unique to AutoGPT: artificial-intelligence, autonomous-agents, claude, gpt. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ## When NOT to use koog - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use AutoGPT - Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. - If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ## Common questions ### What is the difference between koog and AutoGPT? koog: Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-brow. AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. See the comparison table for live GitHub stats and shared categories. ### When should I choose koog over AutoGPT? Choose koog over AutoGPT when koog is primarily Kotlin; AutoGPT is Python; License: koog is Apache-2.0, AutoGPT is Other; Tags unique to koog: agentframework, ai-agents-framework, aiagentframework, android-ai; Also covers Inference & Serving. ### When should I choose AutoGPT over koog? Choose AutoGPT over koog when AutoGPT is primarily Python; koog is Kotlin; License: AutoGPT is Other, koog is Apache-2.0; Tags unique to AutoGPT: artificial-intelligence, autonomous-agents, claude, gpt; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### When should I avoid koog? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid AutoGPT? Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ### Is koog or AutoGPT more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 4,447). Stars measure visibility, not whether either tool fits your constraints. ### Are koog and AutoGPT open source? Yes - both are open-source projects on GitHub (koog: Apache-2.0, AutoGPT: Other). ### Where can I find alternatives to koog or AutoGPT? GraphCanon lists graph-backed alternatives at [koog alternatives](/tools/jetbrains-koog/alternatives) and [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) ([koog markdown twin](/tools/jetbrains-koog/alternatives.md), [AutoGPT markdown twin](/tools/significant-gravitas-autogpt/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/jetbrains-koog-vs-significant-gravitas-autogpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, koog or AutoGPT? koog: Active. AutoGPT: 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 koog and AutoGPT? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [koog trust report](/tools/jetbrains-koog/trust); [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=jetbrains-koog`](/api/graphcanon/graph?tool=jetbrains-koog) - 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/_