--- title: "AudioGPT vs FunASR" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aigc-audio-audiogpt-vs-modelscope-funasr" tools: ["aigc-audio-audiogpt", "modelscope-funasr"] --- # AudioGPT vs FunASR *GraphCanon updated Aug 16, 2026* ## Verdict Pick AudioGPT if audioGPT is a Python-based tool for generating and understanding various audio forms including speech, music, sound effects, and talking head animations using pre-trained models; pick FunASR if funASR is an industrial-grade toolkit supporting real-time speech recognition across over 50 languages. [AudioGPT](https://huggingface.co/spaces/AIGC-Audio/AudioGPT) reports 10k GitHub stars, 850 forks, and 53 open issues, last pushed Jul 6, 2024. [FunASR](https://github.com/modelscope/FunASR) has 20k stars, 2.0k forks, and 5 open issues, last pushed Jul 30, 2026. Figures are from public GitHub metadata via [AudioGPT's repository](https://github.com/AIGC-Audio/AudioGPT) and [FunASR's repository](https://github.com/modelscope/FunASR). | | [AudioGPT](/tools/aigc-audio-audiogpt.md) | [FunASR](/tools/modelscope-funasr.md) | | --- | --- | --- | | Tagline | AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head | Industrial-grade speech recognition toolkit | | Stars | 10,172 | 19,554 | | Forks | 850 | 1,965 | | Open issues | 53 | 5 | | Language | Python | Python | | Adopt for | AudioGPT is a Python-based tool for generating and understanding various audio forms including speech, music, sound effects, and talking head animations using pre-trained models. | FunASR is an industrial-grade toolkit supporting real-time speech recognition across over 50 languages. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT License allows free use and modification. | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AudioGPT](/tools/aigc-audio-audiogpt.md) | [FunASR](/tools/modelscope-funasr.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 769d | 0d | | Open issues (now) | 53 | 5 | | Stars delta | +3 (30d) | Unknown | | Open issues delta | -1 (30d) | Unknown | | Full report | [trust report](/tools/aigc-audio-audiogpt/trust.md) | [trust report](/tools/modelscope-funasr/trust.md) | ## Decision facts: AudioGPT - **Adopt for:** AudioGPT is a Python-based tool for generating and understanding various audio forms including speech, music, sound effects, and talking head animations using pre-trained models. ## Decision facts: FunASR - **Requirements:** Requires Python ≥ 3.8.; PyTorch and torchaudio must be installed separately before running FunASR. - **Adopt for:** FunASR is an industrial-grade toolkit supporting real-time speech recognition across over 50 languages. - **License detail:** MIT License allows free use and modification. - **Runtime:** unknown ## Choose when ### Choose AudioGPT if… - License: AudioGPT is Other, FunASR is MIT. - Tags unique to AudioGPT: gpt, music, sound, speech. - - Utilize AudioGPT when you need to generate speech or music with specific style transfer capabilities using GenerSpeech. ### Choose FunASR if… - License: FunASR is MIT, AudioGPT is Other. - Requirements: Requires Python ≥ 3.8.; PyTorch and torchaudio must be installed separately before running FunASR.. - Tags unique to FunASR: asr, chinese, emotion-recognition, multilingual-asr. - When requiring high-speed real-time processing of up to 170x realtime speech recognition. ## When NOT to use AudioGPT - - Avoid AudioGPT if your audio processing toolkit needs to be exclusively self-contained; some model references are external links requiring separate access. - - Do not use for projects that absolutely need completed features for all tasks as certain capabilities (speech translation) are still work-in-progress. ## When NOT to use FunASR - In scenarios where only a narrow set of languages are required, as overhead for supporting over 50 languages may be unnecessary. - For projects lacking GPU resources since certain models, like the Fun-ASR-Nano flagship model, require a GPU to run effectively. ## Common questions ### What is the difference between AudioGPT and FunASR? AudioGPT: AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head. FunASR: Industrial-grade speech recognition toolkit. See the comparison table for live GitHub stats and shared categories. ### When should I choose AudioGPT over FunASR? Choose AudioGPT over FunASR when License: AudioGPT is Other, FunASR is MIT; Tags unique to AudioGPT: gpt, music, sound, speech; - Utilize AudioGPT when you need to generate speech or music with specific style transfer capabilities using GenerSpeech. ### When should I choose FunASR over AudioGPT? Choose FunASR over AudioGPT when License: FunASR is MIT, AudioGPT is Other; Requirements: Requires Python ≥ 3.8.; PyTorch and torchaudio must be installed separately before running FunASR.; Tags unique to FunASR: asr, chinese, emotion-recognition, multilingual-asr; When requiring high-speed real-time processing of up to 170x realtime speech recognition. ### When should I avoid AudioGPT? - Avoid AudioGPT if your audio processing toolkit needs to be exclusively self-contained; some model references are external links requiring separate access. - Do not use for projects that absolutely need completed features for all tasks as certain capabilities (speech translation) are still work-in-progress. ### When should I avoid FunASR? In scenarios where only a narrow set of languages are required, as overhead for supporting over 50 languages may be unnecessary. For projects lacking GPU resources since certain models, like the Fun-ASR-Nano flagship model, require a GPU to run effectively. ### Is AudioGPT or FunASR more popular on GitHub? FunASR has more GitHub stars (19,554 vs 10,172). Stars measure visibility, not whether either tool fits your constraints. ### Are AudioGPT and FunASR open source? Yes - both are open-source projects on GitHub (AudioGPT: Other, FunASR: MIT). ### Where can I find alternatives to AudioGPT or FunASR? GraphCanon lists graph-backed alternatives at [AudioGPT alternatives](/tools/aigc-audio-audiogpt/alternatives) and [FunASR alternatives](/tools/modelscope-funasr/alternatives) ([AudioGPT markdown twin](/tools/aigc-audio-audiogpt/alternatives.md), [FunASR markdown twin](/tools/modelscope-funasr/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/aigc-audio-audiogpt-vs-modelscope-funasr.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AudioGPT or FunASR? AudioGPT: Dormant. FunASR: 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 AudioGPT and FunASR? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AudioGPT trust report](/tools/aigc-audio-audiogpt/trust); [FunASR trust report](/tools/modelscope-funasr/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aigc-audio-audiogpt`](/api/graphcanon/graph?tool=aigc-audio-audiogpt) - 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/_