--- title: "FunClip vs AutoGPT" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/modelscope-funclip-vs-significant-gravitas-autogpt" tools: ["modelscope-funclip", "significant-gravitas-autogpt"] --- # FunClip vs AutoGPT *GraphCanon updated Jul 11, 2026* ## Verdict Pick FunClip when license: FunClip is MIT, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, FunClip is MIT. [FunClip](https://www.funasr.com) reports 5.9k GitHub stars, 710 forks, and 0 open issues, last pushed Jul 7, 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 [FunClip's repository](https://github.com/modelscope/FunClip) and [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT). | | [FunClip](/tools/modelscope-funclip.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Tagline | FunASR-powered video transcription, subtitle generation, and LLM-assisted clipping tool with a local Gradio UI. | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | | Stars | 5,906 | 185,464 | | Forks | 710 | 46,111 | | Open issues | 0 | 494 | | Language | Python | 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 | MIT | Other | | Categories | Computer Vision, LLM Frameworks, Speech & Audio | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FunClip](/tools/modelscope-funclip.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Days since push | 4d | 0d | | Open issues (now) | 0 | 494 | | Security scan | 87 low (87 low) | No lockfile | | Full report | [trust report](/tools/modelscope-funclip/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 FunClip if… - License: FunClip is MIT, AutoGPT is Other. - Tags unique to FunClip: ai-tools, ai-video-editing, asr, auto-subtitles. - Also covers Computer Vision, Speech & Audio. ### Choose AutoGPT if… - License: AutoGPT is Other, FunClip is MIT. - Tags unique to AutoGPT: agentic-ai, agents, ai, artificial-intelligence. - Also covers AI Agents. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ## When NOT to use FunClip - 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 FunClip and AutoGPT? FunClip: FunASR-powered video transcription, subtitle generation, and LLM-assisted clipping tool with a local Gradio UI.. 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 FunClip over AutoGPT? Choose FunClip over AutoGPT when License: FunClip is MIT, AutoGPT is Other; Tags unique to FunClip: ai-tools, ai-video-editing, asr, auto-subtitles; Also covers Computer Vision, Speech & Audio. ### When should I choose AutoGPT over FunClip? Choose AutoGPT over FunClip when License: AutoGPT is Other, FunClip is MIT; Tags unique to AutoGPT: agentic-ai, agents, ai, artificial-intelligence; Also covers AI Agents; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### When should I avoid FunClip? 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 FunClip or AutoGPT more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 5,906). Stars measure visibility, not whether either tool fits your constraints. ### Are FunClip and AutoGPT open source? Yes - both are open-source projects on GitHub (FunClip: MIT, AutoGPT: Other). ### Where can I find alternatives to FunClip or AutoGPT? GraphCanon lists graph-backed alternatives at [FunClip alternatives](/tools/modelscope-funclip/alternatives) and [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) ([FunClip markdown twin](/tools/modelscope-funclip/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/modelscope-funclip-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, FunClip or AutoGPT? FunClip: Very 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 FunClip and AutoGPT? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FunClip trust report](/tools/modelscope-funclip/trust); [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=modelscope-funclip`](/api/graphcanon/graph?tool=modelscope-funclip) - 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/_