--- title: "agentos vs thinkgpt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/framerslab-agentos-vs-jina-ai-thinkgpt" tools: ["framerslab-agentos", "jina-ai-thinkgpt"] --- # agentos vs thinkgpt *GraphCanon updated Aug 23, 2026* ## Verdict Pick agentos if agentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript; pick thinkgpt if thinkGPT stands out for its specialization in agent techniques to expand the abilities of large language models, offering unique value through Python integration under an Apache-2.0 license. [agentos](https://docs.agentos.sh) reports 617 GitHub stars, 92 forks, and 10 open issues, last pushed Aug 7, 2026. [thinkgpt](https://github.com/jina-ai/thinkgpt) has 1.6k stars, 132 forks, and 16 open issues, last pushed May 23, 2024. Figures are from public GitHub metadata via [agentos's repository](https://github.com/framerslab/agentos) and [thinkgpt's repository](https://github.com/jina-ai/thinkgpt). | | [agentos](/tools/framerslab-agentos.md) | [thinkgpt](/tools/jina-ai-thinkgpt.md) | | --- | --- | --- | | Tagline | TypeScript AI agent framework providing cognitive memory and runtime tool forging with support for multi-agent orchestration | Agent techniques to augment your LLM and push it beyond its limits | | Stars | 617 | 1,581 | | Forks | 92 | 132 | | Open issues | 10 | 16 | | Language | TypeScript | Python | | Adopt for | AgentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript. | ThinkGPT stands out for its specialization in agent techniques to expand the abilities of large language models, offering unique value through Python integration under an Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | ThinkGPT is released under the permissive Apache-2.0 license. | | Categories | AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentos](/tools/framerslab-agentos.md) | [thinkgpt](/tools/jina-ai-thinkgpt.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 15d | 806d | | Open issues (now) | 10 | 16 | | Stars delta | +16 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Full report | [trust report](/tools/framerslab-agentos/trust.md) | [trust report](/tools/jina-ai-thinkgpt/trust.md) | ## Decision facts: agentos - **Adopt for:** AgentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript. ## Decision facts: thinkgpt - **Pricing:** freemium - Open source with no direct costs, but may require resource investment for setup and maintenance. - **Requirements:** Min 4 GB RAM; Python environment is necessary. No Docker container required. - **Adopt for:** ThinkGPT stands out for its specialization in agent techniques to expand the abilities of large language models, offering unique value through Python integration under an Apache-2.0 license. - **License detail:** ThinkGPT is released under the permissive Apache-2.0 license. ## Choose when ### Choose agentos if… - agentos is primarily TypeScript; thinkgpt is Python. - Tags unique to agentos: agent-framework, cognitive-memory, llm-orchestration, multi-agent. - Need for cognitive memory and real-time tool generation in AI agents ### Choose thinkgpt if… - thinkgpt is primarily Python; agentos is TypeScript. - Pricing: Open source with no direct costs, but may require resource investment for setup and maintenance.. - Requirements: Min 4 GB RAM; Python environment is necessary. No Docker container required.. - Tags unique to thinkgpt: agent techniques, llm augmentation, machine learning enhancement, python library. - When you need advanced augmentation for your existing language model capabilities with an emphasis on agent-based techniques. ## When NOT to use agentos - Preferring frameworks without multi-agent orchestration support - Prioritizing environments with less than eleven LLM provider options ## When NOT to use thinkgpt - If your project requires direct access to pre-built agent components from other libraries (e.g., LangChain), as ThinkGPT focuses on its own augmentation approach. - In scenarios where integration with proprietary or closed-source systems is required, given ThinkGPT's open-source nature under the Apache-2.0 license. ## Common questions ### What is the difference between agentos and thinkgpt? agentos: TypeScript AI agent framework providing cognitive memory and runtime tool forging with support for multi-agent orchestration. thinkgpt: Agent techniques to augment your LLM and push it beyond its limits. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentos over thinkgpt? Choose agentos over thinkgpt when agentos is primarily TypeScript; thinkgpt is Python; Tags unique to agentos: agent-framework, cognitive-memory, llm-orchestration, multi-agent; Need for cognitive memory and real-time tool generation in AI agents. ### When should I choose thinkgpt over agentos? Choose thinkgpt over agentos when thinkgpt is primarily Python; agentos is TypeScript; Pricing: Open source with no direct costs, but may require resource investment for setup and maintenance.; Requirements: Min 4 GB RAM; Python environment is necessary. No Docker container required.; Tags unique to thinkgpt: agent techniques, llm augmentation, machine learning enhancement, python library; When you need advanced augmentation for your existing language model capabilities with an emphasis on agent-based techniques. ### When should I avoid agentos? Preferring frameworks without multi-agent orchestration support Prioritizing environments with less than eleven LLM provider options ### When should I avoid thinkgpt? If your project requires direct access to pre-built agent components from other libraries (e.g., LangChain), as ThinkGPT focuses on its own augmentation approach. In scenarios where integration with proprietary or closed-source systems is required, given ThinkGPT's open-source nature under the Apache-2.0 license. ### Is agentos or thinkgpt more popular on GitHub? thinkgpt has more GitHub stars (1,581 vs 617). Stars measure visibility, not whether either tool fits your constraints. ### Are agentos and thinkgpt open source? Yes - both are open-source projects on GitHub (agentos: Apache-2.0, thinkgpt: Apache-2.0). ### Where can I find alternatives to agentos or thinkgpt? GraphCanon lists graph-backed alternatives at [agentos alternatives](/tools/framerslab-agentos/alternatives) and [thinkgpt alternatives](/tools/jina-ai-thinkgpt/alternatives) ([agentos markdown twin](/tools/framerslab-agentos/alternatives.md), [thinkgpt markdown twin](/tools/jina-ai-thinkgpt/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/framerslab-agentos-vs-jina-ai-thinkgpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentos or thinkgpt? agentos: Active. thinkgpt: Dormant. 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 agentos and thinkgpt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentos trust report](/tools/framerslab-agentos/trust); [thinkgpt trust report](/tools/jina-ai-thinkgpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=framerslab-agentos`](/api/graphcanon/graph?tool=framerslab-agentos) - 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/_