--- title: "CosyVoice vs Speech" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/funaudiollm-cosyvoice-vs-nvidia-nemo-speech" tools: ["funaudiollm-cosyvoice", "nvidia-nemo-speech"] --- # CosyVoice vs Speech *GraphCanon updated Aug 23, 2026* ## Verdict Pick CosyVoice if cosyVoice is a Python-based multi-lingual large voice generation model. It supports extensive capabilities including fine-tuning, TTS (Text-To-Speech), and natural language generation; pick Speech if nVIDIA-NeMo/Speech - A scalable toolkit for speech AI tasks such as ASR, TTS, and speaker recognition built on PyTorch with CUDA support. [CosyVoice](https://funaudiollm.github.io/cosyvoice3) reports 23k GitHub stars, 2.6k forks, and 719 open issues, last pushed May 25, 2026. [Speech](https://docs.nvidia.com/nemo/speech/nightly/index.html) has 18k stars, 3.5k forks, and 238 open issues, last pushed Aug 7, 2026. Figures are from public GitHub metadata via [CosyVoice's repository](https://github.com/FunAudioLLM/CosyVoice) and [Speech's repository](https://github.com/NVIDIA-NeMo/Speech). | | [CosyVoice](/tools/funaudiollm-cosyvoice.md) | [Speech](/tools/nvidia-nemo-speech.md) | | --- | --- | --- | | Tagline | Multi-lingual large voice generation model with full-stack abilities for inference, training and deployment. | A scalable generative AI framework for Speech AI | | Stars | 22,870 | 17,940 | | Forks | 2,631 | 3,533 | | Open issues | 719 | 238 | | Language | Python | Python | | Adopt for | CosyVoice is a Python-based multi-lingual large voice generation model. It supports extensive capabilities including fine-tuning, TTS (Text-To-Speech), and natural language generation. | NVIDIA-NeMo/Speech - A scalable toolkit for speech AI tasks such as ASR, TTS, and speaker recognition built on PyTorch with CUDA support. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving, Model Training, Speech & Audio | Developer Tools, Model Training, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [CosyVoice](/tools/funaudiollm-cosyvoice.md) | [Speech](/tools/nvidia-nemo-speech.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 89d | 0d | | Open issues (now) | 719 | 238 | | Stars delta | +497 (30d) | Unknown | | Open issues delta | -37 (30d) | Unknown | | Full report | [trust report](/tools/funaudiollm-cosyvoice/trust.md) | [trust report](/tools/nvidia-nemo-speech/trust.md) | ## Shared compatibility - **Python**: [CosyVoice](/tools/funaudiollm-cosyvoice.md) - Python runtime; [Speech](/tools/nvidia-nemo-speech.md) - Python runtime ## Decision facts: CosyVoice - **Adopt for:** CosyVoice is a Python-based multi-lingual large voice generation model. It supports extensive capabilities including fine-tuning, TTS (Text-To-Speech), and natural language generation. ## Decision facts: Speech - **Adopt for:** NVIDIA-NeMo/Speech - A scalable toolkit for speech AI tasks such as ASR, TTS, and speaker recognition built on PyTorch with CUDA support. ## Choose when ### Choose CosyVoice if… - Tags unique to CosyVoice: audio-generation, cantonese, chatbot, chatgpt. - Also covers Inference & Serving. - When you need support for multiple languages like Cantonese, Chinese, English, Japanese, and Korean. ### Choose Speech if… - Tags unique to Speech: asr, deeplearning, generative-ai, machine-translation. - Also covers Developer Tools. - When working on projects that require extensive GPU utilization for training large models due to its support for efficient CUDA usage. ## When NOT to use CosyVoice - If your project specifically requires fine-tuned performance in languages not supported by CosyVoice such as Arabic or Spanish. - When strict real-time speech synthesis requirements are essential, as CosyVoice may face delays depending on the environment's computational power and model complexity. ## When NOT to use Speech - For environments where GPU access is limited or unavailable since the toolkit highly recommends a GPU setup for both training and recommended for inference. - If your Python/PyTorch/CUDA versions fall below the specified requirements (Python 3.12+, PyTorch 2.7+), as lower versions will not be compatible with NeMo Speech. - In scenarios where you're working with models that do not require or benefit significantly from GPU acceleration, given its architecture optimized for GPU use. ## Common questions ### What is the difference between CosyVoice and Speech? CosyVoice: Multi-lingual large voice generation model with full-stack abilities for inference, training and deployment.. Speech: A scalable generative AI framework for Speech AI. See the comparison table for live GitHub stats and shared categories. ### When should I choose CosyVoice over Speech? Choose CosyVoice over Speech when Tags unique to CosyVoice: audio-generation, cantonese, chatbot, chatgpt; Also covers Inference & Serving; When you need support for multiple languages like Cantonese, Chinese, English, Japanese, and Korean. ### When should I choose Speech over CosyVoice? Choose Speech over CosyVoice when Tags unique to Speech: asr, deeplearning, generative-ai, machine-translation; Also covers Developer Tools; When working on projects that require extensive GPU utilization for training large models due to its support for efficient CUDA usage. ### When should I avoid CosyVoice? If your project specifically requires fine-tuned performance in languages not supported by CosyVoice such as Arabic or Spanish. When strict real-time speech synthesis requirements are essential, as CosyVoice may face delays depending on the environment's computational power and model complexity. ### When should I avoid Speech? For environments where GPU access is limited or unavailable since the toolkit highly recommends a GPU setup for both training and recommended for inference. If your Python/PyTorch/CUDA versions fall below the specified requirements (Python 3.12+, PyTorch 2.7+), as lower versions will not be compatible with NeMo Speech. In scenarios where you're working with models that do not require or benefit significantly from GPU acceleration, given its architecture optimized for GPU use. ### Is CosyVoice or Speech more popular on GitHub? CosyVoice has more GitHub stars (22,870 vs 17,940). Stars measure visibility, not whether either tool fits your constraints. ### Are CosyVoice and Speech open source? Yes - both are open-source projects on GitHub (CosyVoice: Apache-2.0, Speech: Apache-2.0). ### Where can I find alternatives to CosyVoice or Speech? GraphCanon lists graph-backed alternatives at [CosyVoice alternatives](/tools/funaudiollm-cosyvoice/alternatives) and [Speech alternatives](/tools/nvidia-nemo-speech/alternatives) ([CosyVoice markdown twin](/tools/funaudiollm-cosyvoice/alternatives.md), [Speech markdown twin](/tools/nvidia-nemo-speech/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/funaudiollm-cosyvoice-vs-nvidia-nemo-speech.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, CosyVoice or Speech? CosyVoice: Steady. Speech: 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 CosyVoice and Speech? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [CosyVoice trust report](/tools/funaudiollm-cosyvoice/trust); [Speech trust report](/tools/nvidia-nemo-speech/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=funaudiollm-cosyvoice`](/api/graphcanon/graph?tool=funaudiollm-cosyvoice) - 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/_