Comparison
Chinese-LLaMA-Alpaca vs ChatGLM-6B
Verdict
Pick Chinese-LLaMA-Alpaca if chinese-LLaMA-Alpaca offers Chinese versions of LLaMA and Alpaca models, with expanded Chinese vocabulary and pre-training on Chinese data, supporting local deployment on CPU/GPU; 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 efficient fine-.
Markdown twin · Chinese-LLaMA-Alpaca alternatives · ChatGLM-6B alternatives
GraphCanon updated Sep 20, 2026
7views this month
vs
Trust & integrity
| Signal | Chinese-LLaMA-Alpaca | ChatGLM-6B |
|---|---|---|
| Maintenance | Slowing (152d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (813d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | Published findings As of Sep 18, 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
- Chinese-LLaMA-Alpaca
- Chinese LLaMA & Alpaca LLMs
- ChatGLM-6B
- An Open Bilingual Dialogue Language Model
Stars
- Chinese-LLaMA-Alpaca
- 19k
- ChatGLM-6B
- 41k
Forks
- Chinese-LLaMA-Alpaca
- 1.8k
- ChatGLM-6B
- 5.1k
Open issues
- Chinese-LLaMA-Alpaca
- 5
- ChatGLM-6B
- 605
Language
- Chinese-LLaMA-Alpaca
- Python
- ChatGLM-6B
- Python
Adopt for
- Chinese-LLaMA-Alpaca
- Chinese-LLaMA-Alpaca offers Chinese versions of LLaMA and Alpaca models, with expanded Chinese vocabulary and pre-training on Chinese data, supporting local deployment on CPU/GPU.
- ChatGLM-6B
- 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
- Chinese-LLaMA-Alpaca
- -
- ChatGLM-6B
- -
Runtime
- Chinese-LLaMA-Alpaca
- -
- ChatGLM-6B
- -
License
- Chinese-LLaMA-Alpaca
- The tool is licensed under Apache-2.0, allowing for free use, modification, and distribution.
- ChatGLM-6B
- Apache-2.0 license, allowing for both academic and free commercial use after registration.
Last pushed
- Chinese-LLaMA-Alpaca
- Apr 19, 2026
- ChatGLM-6B
- Jun 27, 2024
Categories
- Chinese-LLaMA-Alpaca
- Inference & Serving, LLM Frameworks, Model Training
- ChatGLM-6B
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- Chinese-LLaMA-Alpaca
- Slowing (36%)
- ChatGLM-6B
- Dormant (18%)
Days since push
- Chinese-LLaMA-Alpaca
- 152d
- ChatGLM-6B
- 813d
Open issues (now)
- Chinese-LLaMA-Alpaca
- 5
- ChatGLM-6B
- 605
Stars delta
- Chinese-LLaMA-Alpaca
- +10 (30d)
- ChatGLM-6B
- -53 (30d)
Open issues delta
- Chinese-LLaMA-Alpaca
- -1 (30d)
- ChatGLM-6B
- -2 (30d)
Owner type
- Chinese-LLaMA-Alpaca
- User
- ChatGLM-6B
- Organization
Full report
- Chinese-LLaMA-Alpaca
- Trust report
- ChatGLM-6B
- Trust report
Choose Chinese-LLaMA-Alpaca if…
- Pricing: The repository provides free access to the models and scripts, but users may incur costs related to hardware and cloud services for deployment..
- Requirements: Min 8 GB RAM; Requires Python environment.; Supports deployment on local CPU/GPU..
- Tags unique to Chinese-LLaMA-Alpaca: alpaca, llama, llm, lora.
- Also covers Model Training.
- When you need Chinese-specific large language models for tasks that require deep understanding of the Chinese language.
When NOT to use Chinese-LLaMA-Alpaca
- If your project requires models that are not specific to the Chinese language or do not benefit from Chinese-specific pre-training.
- When you need models that are not available in the sizes provided by Chinese-LLaMA-Alpaca, such as models smaller than 7B or larger than 33B.
- If you prefer models that are not based on LLaMA or Alpaca architectures.
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ymcui/Chinese-LLaMA-Alpaca) · observed Sep 20, 2026
- GitHub forks (ymcui/Chinese-LLaMA-Alpaca) · observed Sep 20, 2026
- Last push (ymcui/Chinese-LLaMA-Alpaca) · observed Apr 19, 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 (zai-org/ChatGLM-6B) · observed Sep 20, 2026
- GitHub forks (zai-org/ChatGLM-6B) · observed Sep 20, 2026
- Last push (zai-org/ChatGLM-6B) · observed Jun 27, 2024
- 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 on cards: Chinese-LLaMA-Alpaca 19k · ChatGLM-6B 41k (synced Sep 20, 2026).
Common questions
- What is the difference between Chinese-LLaMA-Alpaca and ChatGLM-6B?
- Chinese-LLaMA-Alpaca: Chinese LLaMA & Alpaca LLMs. ChatGLM-6B: An Open Bilingual Dialogue Language Model. See the comparison table for live GitHub stats and shared categories.
- When should I choose Chinese-LLaMA-Alpaca over ChatGLM-6B?
- Choose Chinese-LLaMA-Alpaca over ChatGLM-6B when Pricing: The repository provides free access to the models and scripts, but users may incur costs related to hardware and cloud services for deployment.; Requirements: Min 8 GB RAM; Requires Python environment.; Supports deployment on local CPU/GPU.; Tags unique to Chinese-LLaMA-Alpaca: alpaca, llama, llm, lora; Also covers Model Training; When you need Chinese-specific large language models for tasks that require deep understanding of the Chinese language.
- When should I choose ChatGLM-6B over Chinese-LLaMA-Alpaca?
- Choose ChatGLM-6B over Chinese-LLaMA-Alpaca 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 Chinese-LLaMA-Alpaca?
- If your project requires models that are not specific to the Chinese language or do not benefit from Chinese-specific pre-training. When you need models that are not available in the sizes provided by Chinese-LLaMA-Alpaca, such as models smaller than 7B or larger than 33B. If you prefer models that are not based on LLaMA or Alpaca architectures.
- 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 Chinese-LLaMA-Alpaca or ChatGLM-6B more popular on GitHub?
- ChatGLM-6B has more GitHub stars (40,959 vs 18,943). Stars measure visibility, not whether either tool fits your constraints.
- Are Chinese-LLaMA-Alpaca and ChatGLM-6B open source?
- Yes - both are open-source projects on GitHub (Chinese-LLaMA-Alpaca: Apache-2.0, ChatGLM-6B: Apache-2.0).
- Where can I find alternatives to Chinese-LLaMA-Alpaca or ChatGLM-6B?
- GraphCanon lists graph-backed alternatives at Chinese-LLaMA-Alpaca alternatives and ChatGLM-6B alternatives (Chinese-LLaMA-Alpaca markdown twin, ChatGLM-6B 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, Chinese-LLaMA-Alpaca or ChatGLM-6B?
- Chinese-LLaMA-Alpaca: Slowing. 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 Chinese-LLaMA-Alpaca and ChatGLM-6B?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Chinese-LLaMA-Alpaca trust report; ChatGLM-6B trust report.