--- title: "mlx-audio vs Fun-ASR" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/blaizzy-mlx-audio-vs-funaudiollm-fun-asr" tools: ["blaizzy-mlx-audio", "funaudiollm-fun-asr"] --- # mlx-audio vs Fun-ASR *GraphCanon updated Jul 30, 2026* ## Verdict Pick mlx-audio if mlx-audio is designed to offer an efficient speech processing library on Apple's MLX framework for tasks involving TTS, STT, and STS operations; pick Fun-ASR if fun-ASR is a real-time speech recognition tool supporting 31 languages with capabilities for handling dialects, accents, and speaker diarization. [mlx-audio](https://blaizzy.github.io/mlx-audio/) reports 7.6k GitHub stars, 680 forks, and 88 open issues, last pushed Jul 28, 2026. [Fun-ASR](https://huggingface.co/spaces/FunAudioLLM/Fun-ASR-Nano) has 1.4k stars, 141 forks, and 0 open issues, last pushed Jul 24, 2026. Figures are from public GitHub metadata via [mlx-audio's repository](https://github.com/Blaizzy/mlx-audio) and [Fun-ASR's repository](https://github.com/FunAudioLLM/Fun-ASR). | | [mlx-audio](/tools/blaizzy-mlx-audio.md) | [Fun-ASR](/tools/funaudiollm-fun-asr.md) | | --- | --- | --- | | Tagline | A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library on Apple's MLX framework. | Fun-ASR-Nano LLM-ASR model supports 31 languages for real-time speech recognition tasks | | Stars | 7,639 | 1,449 | | Forks | 680 | 141 | | Open issues | 88 | 0 | | Language | Python | C | | Adopt for | mlx-audio is designed to offer an efficient speech processing library on Apple's MLX framework for tasks involving TTS, STT, and STS operations. | Fun-ASR is a real-time speech recognition tool supporting 31 languages with capabilities for handling dialects, accents, and speaker diarization. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Speech & Audio | LLM Frameworks, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mlx-audio](/tools/blaizzy-mlx-audio.md) | [Fun-ASR](/tools/funaudiollm-fun-asr.md) | | --- | --- | --- | | Days since push | 0d | 6d | | Open issues (now) | 88 | 0 | | Owner type | User | Organization | | Full report | [trust report](/tools/blaizzy-mlx-audio/trust.md) | [trust report](/tools/funaudiollm-fun-asr/trust.md) | ## Shared compatibility - **Python**: [mlx-audio](/tools/blaizzy-mlx-audio.md) - Python runtime; [Fun-ASR](/tools/funaudiollm-fun-asr.md) - Python runtime ## Decision facts: mlx-audio - **Adopt for:** mlx-audio is designed to offer an efficient speech processing library on Apple's MLX framework for tasks involving TTS, STT, and STS operations. ## Decision facts: Fun-ASR - **Pricing:** freemium - Open source under Apache License 2.0 allows free use with attribution and adherence to the license terms. - **Requirements:** Installation requires Python packages `funasr` version >=1.3.3, and `vllm` version >=0.12.0. - **Adopt for:** Fun-ASR is a real-time speech recognition tool supporting 31 languages with capabilities for handling dialects, accents, and speaker diarization. - **License detail:** Apache-2.0 ## Choose when ### Choose mlx-audio if… - mlx-audio is primarily Python; Fun-ASR is C. - License: mlx-audio is MIT, Fun-ASR is Apache-2.0. - Tags unique to mlx-audio: apple-silicon, audio-processing, mlx, multimodal. - Use mlx-audio if you require high performance in text-to-speech, speech-to-text, or speech-to-speech transformations specifically optimized for Apple Silicon Macs (M1/M2/M3/M4). ### Choose Fun-ASR if… - Fun-ASR is primarily C; mlx-audio is Python. - License: Fun-ASR is Apache-2.0, mlx-audio is MIT. - Pricing: Open source under Apache License 2.0 allows free use with attribution and adherence to the license terms.. - Requirements: Installation requires Python packages `funasr` version >=1.3.3, and `vllm` version >=0.12.0.. - Tags unique to Fun-ASR: asr, audio-language-model, multilingual-asr, real-time-asr. - Also covers LLM Frameworks. - When you need support for 31 different languages including handling of various dialects and accents. ## When NOT to use mlx-audio - Do not use mlx-audio if your project or target hardware is not based on Apple Silicon. It requires specifically designed optimizations that do not apply to Intel processors. - Avoid mlx-audio when the dependency on ffmpeg for audio format handling becomes a limitation due to licensing, compatibility with existing pipelines, or specific codec requirements. - Do not opt for mlx-audio if your application does not require seamless integration within the MLX framework and does not gain any significant benefit from its specialized support. ## When NOT to use Fun-ASR - Avoid if your project requires a specific programming language other than C as Fun-ASR is primarily developed in C. - If you do not require on-device processing, as this tool is designed for on-device inference which may limit scalability for cloud-based applications. ## Common questions ### What is the difference between mlx-audio and Fun-ASR? mlx-audio: A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library on Apple's MLX framework.. Fun-ASR: Fun-ASR-Nano LLM-ASR model supports 31 languages for real-time speech recognition tasks. See the comparison table for live GitHub stats and shared categories. ### When should I choose mlx-audio over Fun-ASR? Choose mlx-audio over Fun-ASR when mlx-audio is primarily Python; Fun-ASR is C; License: mlx-audio is MIT, Fun-ASR is Apache-2.0; Tags unique to mlx-audio: apple-silicon, audio-processing, mlx, multimodal; Use mlx-audio if you require high performance in text-to-speech, speech-to-text, or speech-to-speech transformations specifically optimized for Apple Silicon Macs (M1/M2/M3/M4). ### When should I choose Fun-ASR over mlx-audio? Choose Fun-ASR over mlx-audio when Fun-ASR is primarily C; mlx-audio is Python; License: Fun-ASR is Apache-2.0, mlx-audio is MIT; Pricing: Open source under Apache License 2.0 allows free use with attribution and adherence to the license terms.; Requirements: Installation requires Python packages `funasr` version >=1.3.3, and `vllm` version >=0.12.0.; Tags unique to Fun-ASR: asr, audio-language-model, multilingual-asr, real-time-asr; Also covers LLM Frameworks; When you need support for 31 different languages including handling of various dialects and accents. ### When should I avoid mlx-audio? Do not use mlx-audio if your project or target hardware is not based on Apple Silicon. It requires specifically designed optimizations that do not apply to Intel processors. Avoid mlx-audio when the dependency on ffmpeg for audio format handling becomes a limitation due to licensing, compatibility with existing pipelines, or specific codec requirements. Do not opt for mlx-audio if your application does not require seamless integration within the MLX framework and does not gain any significant benefit from its specialized support. ### When should I avoid Fun-ASR? Avoid if your project requires a specific programming language other than C as Fun-ASR is primarily developed in C. If you do not require on-device processing, as this tool is designed for on-device inference which may limit scalability for cloud-based applications. ### Is mlx-audio or Fun-ASR more popular on GitHub? mlx-audio has more GitHub stars (7,639 vs 1,449). Stars measure visibility, not whether either tool fits your constraints. ### Are mlx-audio and Fun-ASR open source? Yes - both are open-source projects on GitHub (mlx-audio: MIT, Fun-ASR: Apache-2.0). ### Where can I find alternatives to mlx-audio or Fun-ASR? GraphCanon lists graph-backed alternatives at [mlx-audio alternatives](/tools/blaizzy-mlx-audio/alternatives) and [Fun-ASR alternatives](/tools/funaudiollm-fun-asr/alternatives) ([mlx-audio markdown twin](/tools/blaizzy-mlx-audio/alternatives.md), [Fun-ASR markdown twin](/tools/funaudiollm-fun-asr/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/blaizzy-mlx-audio-vs-funaudiollm-fun-asr.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mlx-audio or Fun-ASR? mlx-audio: Very active. Fun-ASR: 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 mlx-audio and Fun-ASR? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mlx-audio trust report](/tools/blaizzy-mlx-audio/trust); [Fun-ASR trust report](/tools/funaudiollm-fun-asr/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=blaizzy-mlx-audio`](/api/graphcanon/graph?tool=blaizzy-mlx-audio) - 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/_