--- title: "MOSS vs ChatGLM-6B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openmoss-moss-vs-zai-org-chatglm-6b" tools: ["openmoss-moss", "zai-org-chatglm-6b"] --- # MOSS vs ChatGLM-6B *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 ChatGLM-6B if chatGLM-6B is an open-source bilingual dialogue language model with 6.2 billion parameters, optimized for Chinese and English conversations. It supports local deployment with model quantization and offers. [MOSS](https://txsun1997.github.io/blogs/moss.html) reports 12k GitHub stars, 1.1k forks, and 243 open issues, last pushed Sep 6, 2026. [ChatGLM-6B](https://github.com/zai-org/ChatGLM-6B) has 41k stars, 5.1k forks, and 605 open issues, last pushed Jun 27, 2024. Figures are from public GitHub metadata via [MOSS's repository](https://github.com/OpenMOSS/MOSS) and [ChatGLM-6B's repository](https://github.com/zai-org/ChatGLM-6B). | | [MOSS](/tools/openmoss-moss.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Tagline | An open-source, tool-augmented conversational language model from Fudan University | An Open Bilingual Dialogue Language Model | | Stars | 12,253 | 40,959 | | Forks | 1,127 | 5,101 | | Open issues | 243 | 605 | | 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. | ChatGLM-6B is an open-source bilingual dialogue language model with 6.2 billion parameters, optimized for Chinese and English conversations. It supports local deployment with model quantization and offers efficient fine- | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 license, allowing for both academic and free commercial use after registration. | | Categories | Inference & Serving, LLM Frameworks, Model Training | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [MOSS](/tools/openmoss-moss.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 12d | 813d | | Open issues (now) | 243 | 605 | | Stars delta | +39 (30d) | -53 (30d) | | Open issues delta | 0 (30d) | -2 (30d) | | Full report | [trust report](/tools/openmoss-moss/trust.md) | [trust report](/tools/zai-org-chatglm-6b/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: ChatGLM-6B - **Pricing:** freemium - The model weights are completely open for academic research and allow free commercial use after registration. - **Requirements:** Min 8 GB RAM; Local deployment requires a minimum of 6GB of VRAM in INT4 quantization level for inference and 7GB for fine-tuning. - **Adopt for:** ChatGLM-6B is an open-source bilingual dialogue language model with 6.2 billion parameters, optimized for Chinese and English conversations. It supports local deployment with model quantization and offers efficient fine- - **License detail:** Apache-2.0 license, allowing for both academic and free commercial use after registration. ## Choose when ### Choose MOSS if… - Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, large-language-models. - Also covers Model Training. - Use MOSS when you need a conversational language model that supports both Chinese and English dialogue. ### Choose ChatGLM-6B if… - Pricing: The model weights are completely open for academic research and allow free commercial use after registration.. - Requirements: Min 8 GB RAM; Local deployment requires a minimum of 6GB of VRAM in INT4 quantization level for inference and 7GB for fine-tuning.. - Tags unique to ChatGLM-6B: bilingual, commercial-use, dialogue, fine-tuning. - Use ChatGLM-6B when you need a model that is optimized for both Chinese and English conversations, offering a bilingual capability that is particularly strong in these languages. ## 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 ChatGLM-6B - Avoid using ChatGLM-6B if your project requires a model that supports languages other than Chinese and English, as it is specifically optimized for these two languages. - Do not use ChatGLM-6B if you need a model that is larger than 6.2 billion parameters, as it may not provide the depth of understanding or generation capabilities that larger models offer. ## Common questions ### What is the difference between MOSS and ChatGLM-6B? MOSS: An open-source, tool-augmented conversational language model from Fudan University. ChatGLM-6B: An Open Bilingual Dialogue Language Model. See the comparison table for live GitHub stats and shared categories. ### When should I choose MOSS over ChatGLM-6B? Choose MOSS over ChatGLM-6B when Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, large-language-models; Also covers Model Training; Use MOSS when you need a conversational language model that supports both Chinese and English dialogue. ### When should I choose ChatGLM-6B over MOSS? Choose ChatGLM-6B over MOSS when Pricing: The model weights are completely open for academic research and allow free commercial use after registration.; Requirements: Min 8 GB RAM; Local deployment requires a minimum of 6GB of VRAM in INT4 quantization level for inference and 7GB for fine-tuning.; Tags unique to ChatGLM-6B: bilingual, commercial-use, dialogue, fine-tuning; Use ChatGLM-6B when you need a model that is optimized for both Chinese and English conversations, offering a bilingual capability that is particularly strong in these languages. ### 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 ChatGLM-6B? Avoid using ChatGLM-6B if your project requires a model that supports languages other than Chinese and English, as it is specifically optimized for these two languages. Do not use ChatGLM-6B if you need a model that is larger than 6.2 billion parameters, as it may not provide the depth of understanding or generation capabilities that larger models offer. ### Is MOSS or ChatGLM-6B more popular on GitHub? ChatGLM-6B has more GitHub stars (40,959 vs 12,253). Stars measure visibility, not whether either tool fits your constraints. ### Are MOSS and ChatGLM-6B open source? Yes - both are open-source projects on GitHub (MOSS: Apache-2.0, ChatGLM-6B: Apache-2.0). ### Where can I find alternatives to MOSS or ChatGLM-6B? GraphCanon lists graph-backed alternatives at [MOSS alternatives](/tools/openmoss-moss/alternatives) and [ChatGLM-6B alternatives](/tools/zai-org-chatglm-6b/alternatives) ([MOSS markdown twin](/tools/openmoss-moss/alternatives.md), [ChatGLM-6B markdown twin](/tools/zai-org-chatglm-6b/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-zai-org-chatglm-6b.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, MOSS or ChatGLM-6B? MOSS: Active. ChatGLM-6B: Dormant. 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 ChatGLM-6B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [MOSS trust report](/tools/openmoss-moss/trust); [ChatGLM-6B trust report](/tools/zai-org-chatglm-6b/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/_