--- title: "MOSS vs ChatGLM2-6B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openmoss-moss-vs-zai-org-chatglm2-6b" tools: ["openmoss-moss", "zai-org-chatglm2-6b"] --- # MOSS vs ChatGLM2-6B *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 ChatGLM2-6B if chatGLM2-6B is an open-source bilingual chat language model with enhanced performance, longer context length, and efficient inference capabilities. [MOSS](https://txsun1997.github.io/blogs/moss.html) reports 12k GitHub stars, 1.1k forks, and 243 open issues, last pushed Sep 6, 2026. [ChatGLM2-6B](https://github.com/zai-org/ChatGLM2-6B) has 16k stars, 1.8k forks, and 450 open issues, last pushed Jun 27, 2024. Figures are from public GitHub metadata via [MOSS's repository](https://github.com/OpenMOSS/MOSS) and [ChatGLM2-6B's repository](https://github.com/zai-org/ChatGLM2-6B). | | [MOSS](/tools/openmoss-moss.md) | [ChatGLM2-6B](/tools/zai-org-chatglm2-6b.md) | | --- | --- | --- | | Tagline | An open-source, tool-augmented conversational language model from Fudan University | An Open Bilingual Chat LLM | | Stars | 12,253 | 15,517 | | Forks | 1,127 | 1,781 | | Open issues | 243 | 450 | | 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. | ChatGLM2-6B is an open-source bilingual chat language model with enhanced performance, longer context length, and efficient inference capabilities. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The model's weights are completely open for academic research and allow 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) | [ChatGLM2-6B](/tools/zai-org-chatglm2-6b.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 12d | 813d | | Open issues (now) | 243 | 450 | | Stars delta | +39 (30d) | -23 (30d) | | Full report | [trust report](/tools/openmoss-moss/trust.md) | [trust report](/tools/zai-org-chatglm2-6b/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: ChatGLM2-6B - **Pricing:** freemium - The model is free for both academic and commercial use after registration. - **Requirements:** Min 6 GB RAM; The model requires 6GB of GPU memory for inference with INT4 quantization. - **Adopt for:** ChatGLM2-6B is an open-source bilingual chat language model with enhanced performance, longer context length, and efficient inference capabilities. - **License detail:** The model's weights are completely open for academic research and allow free commercial use after registration. ## Choose when ### Choose MOSS if… - License: MOSS is Apache-2.0, ChatGLM2-6B is Other. - Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, natural language processing. - Also covers Model Training. - Use MOSS when you need a conversational language model that supports both Chinese and English dialogue. ### Choose ChatGLM2-6B if… - License: ChatGLM2-6B is Other, MOSS is Apache-2.0. - Pricing: The model is free for both academic and commercial use after registration.. - Requirements: Min 6 GB RAM; The model requires 6GB of GPU memory for inference with INT4 quantization.. - Tags unique to ChatGLM2-6B: chatglm, chatglm-6b, llm. - Use ChatGLM2-6B when you need a bilingual (Chinese-English) chatbot with improved performance metrics over its predecessor, such as higher accuracy on MMLU, CEval, GSM8K, and BBH datasets. ## 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 ChatGLM2-6B - Avoid using ChatGLM2-6B if your application requires a model with a context length shorter than 8K, as the model is optimized for longer context lengths. - Do not use this model if you need a model that is larger than 6B parameters, as ChatGLM2-6B is specifically designed for this size and may not meet the needs of applications requiring larger models. - If your project strictly requires a model that has been tested and proven in a wide range of commercial applications, ChatGLM2-6B might not be the best choice, as it is still under development and its ## Common questions ### What is the difference between MOSS and ChatGLM2-6B? MOSS: An open-source, tool-augmented conversational language model from Fudan University. ChatGLM2-6B: An Open Bilingual Chat LLM. See the comparison table for live GitHub stats and shared categories. ### When should I choose MOSS over ChatGLM2-6B? Choose MOSS over ChatGLM2-6B when License: MOSS is Apache-2.0, ChatGLM2-6B is Other; Tags unique to MOSS: chatgpt, deep-learning, dialogue-systems, natural language processing; Also covers Model Training; Use MOSS when you need a conversational language model that supports both Chinese and English dialogue. ### When should I choose ChatGLM2-6B over MOSS? Choose ChatGLM2-6B over MOSS when License: ChatGLM2-6B is Other, MOSS is Apache-2.0; Pricing: The model is free for both academic and commercial use after registration.; Requirements: Min 6 GB RAM; The model requires 6GB of GPU memory for inference with INT4 quantization.; Tags unique to ChatGLM2-6B: chatglm, chatglm-6b, llm; Use ChatGLM2-6B when you need a bilingual (Chinese-English) chatbot with improved performance metrics over its predecessor, such as higher accuracy on MMLU, CEval, GSM8K, and BBH datasets. ### 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 ChatGLM2-6B? Avoid using ChatGLM2-6B if your application requires a model with a context length shorter than 8K, as the model is optimized for longer context lengths. Do not use this model if you need a model that is larger than 6B parameters, as ChatGLM2-6B is specifically designed for this size and may not meet the needs of applications requiring larger models. If your project strictly requires a model that has been tested and proven in a wide range of commercial applications, ChatGLM2-6B might not be the best choice, as it is still under development and its ### Is MOSS or ChatGLM2-6B more popular on GitHub? ChatGLM2-6B has more GitHub stars (15,517 vs 12,253). Stars measure visibility, not whether either tool fits your constraints. ### Are MOSS and ChatGLM2-6B open source? Yes - both are open-source projects on GitHub (MOSS: Apache-2.0, ChatGLM2-6B: Other). ### Where can I find alternatives to MOSS or ChatGLM2-6B? GraphCanon lists graph-backed alternatives at [MOSS alternatives](/tools/openmoss-moss/alternatives) and [ChatGLM2-6B alternatives](/tools/zai-org-chatglm2-6b/alternatives) ([MOSS markdown twin](/tools/openmoss-moss/alternatives.md), [ChatGLM2-6B markdown twin](/tools/zai-org-chatglm2-6b/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-chatglm2-6b.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, MOSS or ChatGLM2-6B? MOSS: Active. ChatGLM2-6B: 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 ChatGLM2-6B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [MOSS trust report](/tools/openmoss-moss/trust); [ChatGLM2-6B trust report](/tools/zai-org-chatglm2-6b/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/_