Comparison
Chinese-LLaMA-Alpaca-2 vs ChatGLM-6B
Verdict
Pick Chinese-LLaMA-Alpaca-2 if chinese-LLaMA-Alpaca-2 provides Chinese versions of LLaMA-2 and Alpaca-2 large language models, including long context models up to 64K. It includes pretraining and instruction fine-tuning scripts, and supports various部署; 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.
Markdown twin · Chinese-LLaMA-Alpaca-2 alternatives · ChatGLM-6B alternatives
GraphCanon updated Sep 20, 2026
6views this month
vs
Trust & integrity
| Signal | Chinese-LLaMA-Alpaca-2 | 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-2
- Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models
- ChatGLM-6B
- An Open Bilingual Dialogue Language Model
Stars
- Chinese-LLaMA-Alpaca-2
- 7.1k
- ChatGLM-6B
- 41k
Forks
- Chinese-LLaMA-Alpaca-2
- 559
- ChatGLM-6B
- 5.1k
Open issues
- Chinese-LLaMA-Alpaca-2
- 6
- ChatGLM-6B
- 605
Language
- Chinese-LLaMA-Alpaca-2
- Python
- ChatGLM-6B
- Python
Adopt for
- Chinese-LLaMA-Alpaca-2
- Chinese-LLaMA-Alpaca-2 provides Chinese versions of LLaMA-2 and Alpaca-2 large language models, including long context models up to 64K. It includes pretraining and instruction fine-tuning scripts, and supports various部署
- 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-2
- -
- ChatGLM-6B
- -
Runtime
- Chinese-LLaMA-Alpaca-2
- -
- ChatGLM-6B
- -
License
- Chinese-LLaMA-Alpaca-2
- Apache-2.0
- ChatGLM-6B
- Apache-2.0 license, allowing for both academic and free commercial use after registration.
Last pushed
- Chinese-LLaMA-Alpaca-2
- Apr 19, 2026
- ChatGLM-6B
- Jun 27, 2024
Categories
- Chinese-LLaMA-Alpaca-2
- Inference & Serving, LLM Frameworks, Model Training
- ChatGLM-6B
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- Chinese-LLaMA-Alpaca-2
- Slowing (36%)
- ChatGLM-6B
- Dormant (18%)
Days since push
- Chinese-LLaMA-Alpaca-2
- 152d
- ChatGLM-6B
- 813d
Open issues (now)
- Chinese-LLaMA-Alpaca-2
- 6
- ChatGLM-6B
- 605
Stars delta
- Chinese-LLaMA-Alpaca-2
- -6 (30d)
- ChatGLM-6B
- -53 (30d)
Open issues delta
- Chinese-LLaMA-Alpaca-2
- 0 (30d)
- ChatGLM-6B
- -2 (30d)
Owner type
- Chinese-LLaMA-Alpaca-2
- User
- ChatGLM-6B
- Organization
Full report
- Chinese-LLaMA-Alpaca-2
- Trust report
- ChatGLM-6B
- Trust report
Choose Chinese-LLaMA-Alpaca-2 if…
- Tags unique to Chinese-LLaMA-Alpaca-2: 64k, alpaca, alpaca-2, flash-attention.
- Also covers Model Training.
- When you need Chinese-specific large language models with long context capabilities up to 64K.
When NOT to use Chinese-LLaMA-Alpaca-2
- If you need models that support languages other than Chinese, as this repository focuses on Chinese models.
- If you require models with shorter context lengths than 4K, as the standard models support 4K and the long context models support 16K and 64K.
- If you are looking for models that do not include human preference alignment (RLHF), as this repository includes models that have been fine-tuned for this purpose.
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-2) · observed Sep 20, 2026
- GitHub forks (ymcui/Chinese-LLaMA-Alpaca-2) · observed Sep 20, 2026
- Last push (ymcui/Chinese-LLaMA-Alpaca-2) · 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-2 7.1k · ChatGLM-6B 41k (synced Sep 20, 2026).
Common questions
- What is the difference between Chinese-LLaMA-Alpaca-2 and ChatGLM-6B?
- Chinese-LLaMA-Alpaca-2: Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models. 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-2 over ChatGLM-6B?
- Choose Chinese-LLaMA-Alpaca-2 over ChatGLM-6B when Tags unique to Chinese-LLaMA-Alpaca-2: 64k, alpaca, alpaca-2, flash-attention; Also covers Model Training; When you need Chinese-specific large language models with long context capabilities up to 64K.
- When should I choose ChatGLM-6B over Chinese-LLaMA-Alpaca-2?
- Choose ChatGLM-6B over Chinese-LLaMA-Alpaca-2 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-2?
- If you need models that support languages other than Chinese, as this repository focuses on Chinese models. If you require models with shorter context lengths than 4K, as the standard models support 4K and the long context models support 16K and 64K. If you are looking for models that do not include human preference alignment (RLHF), as this repository includes models that have been fine-tuned for this purpose.
- 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-2 or ChatGLM-6B more popular on GitHub?
- ChatGLM-6B has more GitHub stars (40,959 vs 7,118). Stars measure visibility, not whether either tool fits your constraints.
- Are Chinese-LLaMA-Alpaca-2 and ChatGLM-6B open source?
- Yes - both are open-source projects on GitHub (Chinese-LLaMA-Alpaca-2: Apache-2.0, ChatGLM-6B: Apache-2.0).
- Where can I find alternatives to Chinese-LLaMA-Alpaca-2 or ChatGLM-6B?
- GraphCanon lists graph-backed alternatives at Chinese-LLaMA-Alpaca-2 alternatives and ChatGLM-6B alternatives (Chinese-LLaMA-Alpaca-2 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-2 or ChatGLM-6B?
- Chinese-LLaMA-Alpaca-2: 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-2 and ChatGLM-6B?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Chinese-LLaMA-Alpaca-2 trust report; ChatGLM-6B trust report.