--- title: "MOSS vs MOSS-TTS" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openmoss-moss-vs-openmoss-moss-tts" tools: ["openmoss-moss", "openmoss-moss-tts"] --- # MOSS vs MOSS-TTS *GraphCanon updated Sep 20, 2026* ## Verdict Pick MOSS if mOSS is an open-source conversational language model from Fudan University that supports bilingual dialogue and tool invocation. It offers various models, dialogue data, deployment, and fine-tuning code; pick MOSS-TTS if mOSS-TTS, an open-source project for generating high-fidelity audio including speech and sound effects, supports real-time TTS and voice design tasks. [MOSS](https://txsun1997.github.io/blogs/moss.html) reports 12k GitHub stars, 1.1k forks, and 243 open issues, last pushed Sep 6, 2026. [MOSS-TTS](https://mosi.cn/models/moss-tts) has 4.1k stars, 373 forks, and 19 open issues, last pushed Sep 6, 2026. Figures are from public GitHub metadata via [MOSS's repository](https://github.com/OpenMOSS/MOSS) and [MOSS-TTS's repository](https://github.com/OpenMOSS/MOSS-TTS). | | [MOSS](/tools/openmoss-moss.md) | [MOSS-TTS](/tools/openmoss-moss-tts.md) | | --- | --- | --- | | Tagline | An open-source, tool-augmented conversational language model from Fudan University | An open-source speech and sound generation model family designed for high-fidelity scenarios including multi-speaker dialogue。 | | Stars | 12,253 | 4,119 | | Forks | 1,127 | 373 | | Open issues | 243 | 19 | | Language | Python | Python | | Adopt for | MOSS is an open-source conversational language model from Fudan University that supports bilingual dialogue and tool invocation. It offers various models, dialogue data, deployment, and fine-tuning code. | MOSS-TTS, an open-source project for generating high-fidelity audio including speech and sound effects, supports real-time TTS and voice design tasks. | | Persona | - | developer harness | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks, Model Training | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [MOSS](/tools/openmoss-moss.md) | [MOSS-TTS](/tools/openmoss-moss-tts.md) | | --- | --- | --- | | Days since push | 12d | 14d | | Open issues (now) | 243 | 19 | | Stars delta | +39 (30d) | +197 (30d) | | Open issues delta | 0 (30d) | +6 (30d) | | Full report | [trust report](/tools/openmoss-moss/trust.md) | [trust report](/tools/openmoss-moss-tts/trust.md) | ## Decision facts: MOSS - **Adopt for:** MOSS is an open-source conversational language model from Fudan University that supports bilingual dialogue and tool invocation. It offers various models, dialogue data, deployment, and fine-tuning code. ## Decision facts: MOSS-TTS - **Pricing:** freemium - Free to use under the Apache License, version 2.0. - **Adopt for:** MOSS-TTS, an open-source project for generating high-fidelity audio including speech and sound effects, supports real-time TTS and voice design tasks. - **License detail:** Apache-2.0 - **Persona:** developer harness ## Choose when ### Choose MOSS if… - Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, large-language-models. - Also covers Inference & Serving, LLM Frameworks, Model Training. - Use MOSS when you need a conversational language model that supports both Chinese and English dialogue. ### Choose MOSS-TTS if… - Pricing: Free to use under the Apache License, version 2.0.. - Tags unique to MOSS-TTS: audio, llm, multimodal, text-to-speech. - Also covers Speech & Audio. - When developing applications that require complex, high-expressiveness audio scenarios, such as long-form speech or multi-speaker dialogues. ## When NOT to use MOSS - Avoid MOSS if your project requires a model that is not open-source or if you prefer proprietary solutions. - Do not use MOSS if your application does not require support for tool invocation or if you need a model that is not bilingual. - If your project has strict hardware limitations and cannot meet the minimum requirements for running MOSS, such as the need for at least 12GB of GPU memory for the 4-bit quantized version, consider a ## When NOT to use MOSS-TTS - If your project requires minimal dependencies and simple installation processes since MOSS-TTS involves setting up a virtual environment and specific PyTorch versions. - When working on systems with limited GPU capabilities, because MOSS-TTS benefits from but may require certain GPUs for FlashAttention 2 optimizations. ## Common questions ### What is the difference between MOSS and MOSS-TTS? MOSS: An open-source, tool-augmented conversational language model from Fudan University. MOSS-TTS: An open-source speech and sound generation model family designed for high-fidelity scenarios including multi-speaker dialogue。. See the comparison table for live GitHub stats and shared categories. ### When should I choose MOSS over MOSS-TTS? Choose MOSS over MOSS-TTS when Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, large-language-models; Also covers Inference & Serving, LLM Frameworks, Model Training; Use MOSS when you need a conversational language model that supports both Chinese and English dialogue. ### When should I choose MOSS-TTS over MOSS? Choose MOSS-TTS over MOSS when Pricing: Free to use under the Apache License, version 2.0.; Tags unique to MOSS-TTS: audio, llm, multimodal, text-to-speech; Also covers Speech & Audio; When developing applications that require complex, high-expressiveness audio scenarios, such as long-form speech or multi-speaker dialogues. ### When should I avoid MOSS? Avoid MOSS if your project requires a model that is not open-source or if you prefer proprietary solutions. Do not use MOSS if your application does not require support for tool invocation or if you need a model that is not bilingual. If your project has strict hardware limitations and cannot meet the minimum requirements for running MOSS, such as the need for at least 12GB of GPU memory for the 4-bit quantized version, consider a ### When should I avoid MOSS-TTS? If your project requires minimal dependencies and simple installation processes since MOSS-TTS involves setting up a virtual environment and specific PyTorch versions. When working on systems with limited GPU capabilities, because MOSS-TTS benefits from but may require certain GPUs for FlashAttention 2 optimizations. ### Is MOSS or MOSS-TTS more popular on GitHub? MOSS has more GitHub stars (12,253 vs 4,119). Stars measure visibility, not whether either tool fits your constraints. ### Are MOSS and MOSS-TTS open source? Yes - both are open-source projects on GitHub (MOSS: Apache-2.0, MOSS-TTS: Apache-2.0). ### Where can I find alternatives to MOSS or MOSS-TTS? GraphCanon lists graph-backed alternatives at [MOSS alternatives](/tools/openmoss-moss/alternatives) and [MOSS-TTS alternatives](/tools/openmoss-moss-tts/alternatives) ([MOSS markdown twin](/tools/openmoss-moss/alternatives.md), [MOSS-TTS markdown twin](/tools/openmoss-moss-tts/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/openmoss-moss-vs-openmoss-moss-tts.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, MOSS or MOSS-TTS? MOSS: Active. MOSS-TTS: 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 MOSS and MOSS-TTS? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [MOSS trust report](/tools/openmoss-moss/trust); [MOSS-TTS trust report](/tools/openmoss-moss-tts/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openmoss-moss`](/api/graphcanon/graph?tool=openmoss-moss) - 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/_