Comparison
MOSS vs MOSS-TTS
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.
Markdown twin · MOSS alternatives · MOSS-TTS alternatives
GraphCanon updated Sep 20, 2026
10views this month
Trust & integrity
| Signal | MOSS | MOSS-TTS |
|---|---|---|
| Maintenance | Active (12d since push) As of Sep 18, 2026 · github_public_v1 | Active (14d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- 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。
Stars
- MOSS
- 12k
- MOSS-TTS
- 4.1k
Forks
- MOSS
- 1.1k
- MOSS-TTS
- 373
Open issues
- MOSS
- 243
- MOSS-TTS
- 19
Language
- MOSS
- Python
- MOSS-TTS
- Python
Adopt for
- MOSS
- 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
- 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
- MOSS
- -
- MOSS-TTS
- developer harness
Runtime
- MOSS
- -
- MOSS-TTS
- -
License
- MOSS
- Apache-2.0
- MOSS-TTS
- Apache-2.0
Last pushed
- MOSS
- Sep 6, 2026
- MOSS-TTS
- Sep 6, 2026
Categories
- MOSS
- Inference & Serving, LLM Frameworks, Model Training
- MOSS-TTS
- Speech & Audio
Trust and health
Days since push
- MOSS
- 12d
- MOSS-TTS
- 14d
Open issues (now)
- MOSS
- 243
- MOSS-TTS
- 19
Stars delta
- MOSS
- +39 (30d)
- MOSS-TTS
- +197 (30d)
Open issues delta
- MOSS
- 0 (30d)
- MOSS-TTS
- +6 (30d)
OSV dependency advisories
- MOSS
- Published findings
- MOSS-TTS
- No lockfile (source not queried)
Full report
- MOSS
- Trust report
- MOSS-TTS
- Trust report
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.
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
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-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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (OpenMOSS/MOSS) · observed Sep 20, 2026
- GitHub forks (OpenMOSS/MOSS) · observed Sep 20, 2026
- Last push (OpenMOSS/MOSS) · observed Sep 6, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (OpenMOSS/MOSS-TTS) · observed Sep 20, 2026
- GitHub forks (OpenMOSS/MOSS-TTS) · observed Sep 20, 2026
- Last push (OpenMOSS/MOSS-TTS) · observed Sep 6, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: MOSS 12k · MOSS-TTS 4.1k (synced Sep 20, 2026).
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 and MOSS-TTS alternatives (MOSS markdown twin, MOSS-TTS markdown twin), 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 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; MOSS-TTS trust report.