Comparison
Awesome-Chinese-LLM vs Chinese-LLaMA-Alpaca-2
Verdict
Pick Awesome-Chinese-LLM if awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment; pick Chinese-LLaMA-Alpaca-2 if chinese-LLaMA-Alpaca-2 provides Chinese-specific versions of LLaMA-2 and Alpaca-2 with extended context lengths up to 64K tokens.
Markdown twin · Awesome-Chinese-LLM alternatives · Chinese-LLaMA-Alpaca-2 alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | Awesome-Chinese-LLM | Chinese-LLaMA-Alpaca-2 |
|---|---|---|
| Maintenance | Slowing (98d since push) As of 2d · github_public_v1 | Slowing (120d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2d · github_public_v1 | Not a fork · Personal account As of 2d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · 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
- Awesome-Chinese-LLM
- 整理开源的中文大语言模型
- Chinese-LLaMA-Alpaca-2
- Chinese LLaMA-2 & Alpaca-2 models with extended context lengths
Stars
- Awesome-Chinese-LLM
- 23k
- Chinese-LLaMA-Alpaca-2
- 7.1k
Forks
- Awesome-Chinese-LLM
- 2.1k
- Chinese-LLaMA-Alpaca-2
- 562
Open issues
- Awesome-Chinese-LLM
- 27
- Chinese-LLaMA-Alpaca-2
- 6
Language
- Awesome-Chinese-LLM
- -
- Chinese-LLaMA-Alpaca-2
- Python
Adopt for
- Awesome-Chinese-LLM
- Awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment.
- Chinese-LLaMA-Alpaca-2
- Chinese-LLaMA-Alpaca-2 provides Chinese-specific versions of LLaMA-2 and Alpaca-2 with extended context lengths up to 64K tokens.
Persona
- Awesome-Chinese-LLM
- -
- Chinese-LLaMA-Alpaca-2
- -
Runtime
- Awesome-Chinese-LLM
- -
- Chinese-LLaMA-Alpaca-2
- -
License
- Awesome-Chinese-LLM
- -
- Chinese-LLaMA-Alpaca-2
- Apache-2.0
Last pushed
- Awesome-Chinese-LLM
- May 10, 2026
- Chinese-LLaMA-Alpaca-2
- Apr 19, 2026
Categories
- Awesome-Chinese-LLM
- LLM Frameworks, Model Training
- Chinese-LLaMA-Alpaca-2
- LLM Frameworks
Trust and health
Days since push
- Awesome-Chinese-LLM
- 98d
- Chinese-LLaMA-Alpaca-2
- 120d
Open issues (now)
- Awesome-Chinese-LLM
- 27
- Chinese-LLaMA-Alpaca-2
- 6
Stars delta
- Awesome-Chinese-LLM
- +53 (30d)
- Chinese-LLaMA-Alpaca-2
- -8 (30d)
Open issues delta
- Awesome-Chinese-LLM
- +3 (30d)
- Chinese-LLaMA-Alpaca-2
- 0 (30d)
OSV dependency advisories
- Awesome-Chinese-LLM
- No lockfile (source not queried)
- Chinese-LLaMA-Alpaca-2
- Published findings
Full report
- Awesome-Chinese-LLM
- Trust report
- Chinese-LLaMA-Alpaca-2
- Trust report
Shared compatibility
- LangChain · Awesome-Chinese-LLM: LangChain integration · Chinese-LLaMA-Alpaca-2: LangChain integration
Choose Awesome-Chinese-LLM if…
- Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, llama, llm.
- Also covers Model Training.
- If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately.
When NOT to use Awesome-Chinese-LLM
- Avoid if your project necessitates large-scale, highly advanced computational capabilities or you are working with languages other than Chinese.
- If your deployment scenario is limited to public cloud services only without the option for private deployment.
Choose Chinese-LLaMA-Alpaca-2 if…
- Tags unique to Chinese-LLaMA-Alpaca-2: flash-attention, large language model (llm), long context models.
- When you need advanced models specifically tailored for the Chinese language, offering better performance compared to generic models
- Leaner open-issue backlog (6).
When NOT to use Chinese-LLaMA-Alpaca-2
- If your project requires support for languages other than Chinese, as the focus is on refining Chinese text understanding and generation
- In scenarios where shorter context lengths (less than 16K tokens) are sufficient, as the extended models may be overkill in terms of resource usage
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (AiHubCN/Awesome-Chinese-LLM) · observed Aug 17, 2026
- GitHub forks (AiHubCN/Awesome-Chinese-LLM) · observed Aug 17, 2026
- Last push (AiHubCN/Awesome-Chinese-LLM) · observed May 10, 2026
- License file (unknown) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ymcui/Chinese-LLaMA-Alpaca-2) · observed Aug 17, 2026
- GitHub forks (ymcui/Chinese-LLaMA-Alpaca-2) · observed Aug 17, 2026
- Last push (ymcui/Chinese-LLaMA-Alpaca-2) · observed Apr 19, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Awesome-Chinese-LLM 23k · Chinese-LLaMA-Alpaca-2 7.1k (synced Aug 17, 2026).
Common questions
- What is the difference between Awesome-Chinese-LLM and Chinese-LLaMA-Alpaca-2?
- Awesome-Chinese-LLM: 整理开源的中文大语言模型. Chinese-LLaMA-Alpaca-2: Chinese LLaMA-2 & Alpaca-2 models with extended context lengths. See the comparison table for live GitHub stats and shared categories.
- When should I choose Awesome-Chinese-LLM over Chinese-LLaMA-Alpaca-2?
- Choose Awesome-Chinese-LLM over Chinese-LLaMA-Alpaca-2 when Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, llama, llm; Also covers Model Training; If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately.
- When should I choose Chinese-LLaMA-Alpaca-2 over Awesome-Chinese-LLM?
- Choose Chinese-LLaMA-Alpaca-2 over Awesome-Chinese-LLM when Tags unique to Chinese-LLaMA-Alpaca-2: flash-attention, large language model (llm), long context models; When you need advanced models specifically tailored for the Chinese language, offering better performance compared to generic models; Leaner open-issue backlog (6).
- When should I avoid Awesome-Chinese-LLM?
- Avoid if your project necessitates large-scale, highly advanced computational capabilities or you are working with languages other than Chinese. If your deployment scenario is limited to public cloud services only without the option for private deployment.
- When should I avoid Chinese-LLaMA-Alpaca-2?
- If your project requires support for languages other than Chinese, as the focus is on refining Chinese text understanding and generation In scenarios where shorter context lengths (less than 16K tokens) are sufficient, as the extended models may be overkill in terms of resource usage
- Is Awesome-Chinese-LLM or Chinese-LLaMA-Alpaca-2 more popular on GitHub?
- Awesome-Chinese-LLM has more GitHub stars (22,738 vs 7,124). Stars measure visibility, not whether either tool fits your constraints.
- Are Awesome-Chinese-LLM and Chinese-LLaMA-Alpaca-2 open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Awesome-Chinese-LLM or Chinese-LLaMA-Alpaca-2?
- GraphCanon lists graph-backed alternatives at Awesome-Chinese-LLM alternatives and Chinese-LLaMA-Alpaca-2 alternatives (Awesome-Chinese-LLM markdown twin, Chinese-LLaMA-Alpaca-2 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, Awesome-Chinese-LLM or Chinese-LLaMA-Alpaca-2?
- Awesome-Chinese-LLM: Slowing. Chinese-LLaMA-Alpaca-2: Slowing. 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 Awesome-Chinese-LLM and Chinese-LLaMA-Alpaca-2?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-Chinese-LLM trust report; Chinese-LLaMA-Alpaca-2 trust report.