--- title: "BELLE vs ChatGLM-6B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lianjiatech-belle-vs-zai-org-chatglm-6b" tools: ["lianjiatech-belle", "zai-org-chatglm-6b"] --- # BELLE vs ChatGLM-6B *GraphCanon updated Sep 20, 2026* ## Verdict Pick BELLE if bELLE is an open-source Chinese dialogue large model project that focuses on making high-quality instruction-following language models accessible to everyone. It provides instruction training data, models, training 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. [BELLE](https://github.com/LianjiaTech/BELLE) reports 8.3k GitHub stars, 755 forks, and 106 open issues, last pushed Oct 16, 2024. [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 [BELLE's repository](https://github.com/LianjiaTech/BELLE) and [ChatGLM-6B's repository](https://github.com/zai-org/ChatGLM-6B). | | [BELLE](/tools/lianjiatech-belle.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Tagline | Open-source Chinese dialogue large model | An Open Bilingual Dialogue Language Model | | Stars | 8,270 | 40,959 | | Forks | 755 | 5,101 | | Open issues | 106 | 605 | | Language | HTML | Python | | Adopt for | BELLE is an open-source Chinese dialogue large model project that focuses on making high-quality instruction-following language models accessible to everyone. It provides instruction training data, models, training 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 | BELLE is licensed under Apache-2.0, allowing for free use, modification, and distribution. | Apache-2.0 license, allowing for both academic and free commercial use after registration. | | Categories | Computer Vision, Evaluation & Observability, LLM Frameworks, Model Training, Speech & Audio | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [BELLE](/tools/lianjiatech-belle.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Days since push | 701d | 813d | | Open issues (now) | 106 | 605 | | Stars delta | -10 (30d) | -53 (30d) | | Open issues delta | 0 (30d) | -2 (30d) | | Full report | [trust report](/tools/lianjiatech-belle/trust.md) | [trust report](/tools/zai-org-chatglm-6b/trust.md) | ## Shared compatibility - **ChatGPT**: [BELLE](/tools/lianjiatech-belle.md) - Works with ChatGPT; [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) - Works with ChatGPT ## Decision facts: BELLE - **Requirements:** Min 8 GB RAM; Requires Docker; BELLE requires Docker for running the environment.; Ensure you have sufficient computational resources for training and inference. - **Adopt for:** BELLE is an open-source Chinese dialogue large model project that focuses on making high-quality instruction-following language models accessible to everyone. It provides instruction training data, models, training code, - **License detail:** BELLE is licensed under Apache-2.0, allowing for free use, modification, and distribution. ## 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 BELLE if… - BELLE is primarily HTML; ChatGLM-6B is Python. - Requirements: Min 8 GB RAM; Requires Docker; BELLE requires Docker for running the environment.; Ensure you have sufficient computational resources for training and inference.. - Tags unique to BELLE: bloom, chinese-nlp, gpt-evaluation, gpt-q. - Also covers Computer Vision, Evaluation & Observability, Model Training, Speech & Audio. - Use BELLE when you need a Chinese-specific large language model that has been optimized for instruction-following tasks. ### Choose ChatGLM-6B if… - ChatGLM-6B is primarily Python; BELLE is HTML. - 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. - Also covers Inference & Serving. - 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 BELLE - Avoid BELLE if your project requires a language model that is not focused on Chinese, as it is specifically optimized for the Chinese language. - Do not use BELLE if you need a model that is trained on a diverse set of data beyond Chinese dialogue, as it primarily uses data generated by ChatGPT. - BELLE may not be suitable if you require a model that has not been fine-tuned on high-quality dialogue data, as it emphasizes instruction-following capabilities. ## 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 BELLE and ChatGLM-6B? BELLE: Open-source Chinese dialogue large model. ChatGLM-6B: An Open Bilingual Dialogue Language Model. See the comparison table for live GitHub stats and shared categories. ### When should I choose BELLE over ChatGLM-6B? Choose BELLE over ChatGLM-6B when BELLE is primarily HTML; ChatGLM-6B is Python; Requirements: Min 8 GB RAM; Requires Docker; BELLE requires Docker for running the environment.; Ensure you have sufficient computational resources for training and inference.; Tags unique to BELLE: bloom, chinese-nlp, gpt-evaluation, gpt-q; Also covers Computer Vision, Evaluation & Observability, Model Training, Speech & Audio; Use BELLE when you need a Chinese-specific large language model that has been optimized for instruction-following tasks. ### When should I choose ChatGLM-6B over BELLE? Choose ChatGLM-6B over BELLE when ChatGLM-6B is primarily Python; BELLE is HTML; 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; Also covers Inference & Serving; 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 BELLE? Avoid BELLE if your project requires a language model that is not focused on Chinese, as it is specifically optimized for the Chinese language. Do not use BELLE if you need a model that is trained on a diverse set of data beyond Chinese dialogue, as it primarily uses data generated by ChatGPT. BELLE may not be suitable if you require a model that has not been fine-tuned on high-quality dialogue data, as it emphasizes instruction-following capabilities. ### 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 BELLE or ChatGLM-6B more popular on GitHub? ChatGLM-6B has more GitHub stars (40,959 vs 8,270). Stars measure visibility, not whether either tool fits your constraints. ### Are BELLE and ChatGLM-6B open source? Yes - both are open-source projects on GitHub (BELLE: Apache-2.0, ChatGLM-6B: Apache-2.0). ### Where can I find alternatives to BELLE or ChatGLM-6B? GraphCanon lists graph-backed alternatives at [BELLE alternatives](/tools/lianjiatech-belle/alternatives) and [ChatGLM-6B alternatives](/tools/zai-org-chatglm-6b/alternatives) ([BELLE markdown twin](/tools/lianjiatech-belle/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/lianjiatech-belle-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, BELLE or ChatGLM-6B? BELLE: Dormant. 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 BELLE and ChatGLM-6B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [BELLE trust report](/tools/lianjiatech-belle/trust); [ChatGLM-6B trust report](/tools/zai-org-chatglm-6b/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lianjiatech-belle`](/api/graphcanon/graph?tool=lianjiatech-belle) - 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/_