Comparison
Aquila2 vs Chinese-LLaMA-Alpaca
Verdict
Pick Aquila2 if official suite for Aquila2 series LLM by BAAI; 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.
Markdown twin · Aquila2 alternatives · Chinese-LLaMA-Alpaca alternatives
GraphCanon updated Sep 20, 2026
11views this month
vs
Trust & integrity
| Signal | Aquila2 | Chinese-LLaMA-Alpaca |
|---|---|---|
| Maintenance | Dormant (708d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (152d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 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
- Aquila2
- Official repository for Aquila2 series large language models by BAAI
- Chinese-LLaMA-Alpaca
- Chinese LLaMA & Alpaca LLMs
Stars
- Aquila2
- 445
- Chinese-LLaMA-Alpaca
- 19k
Forks
- Aquila2
- 32
- Chinese-LLaMA-Alpaca
- 1.8k
Open issues
- Aquila2
- 2
- Chinese-LLaMA-Alpaca
- 5
Language
- Aquila2
- Python
- Chinese-LLaMA-Alpaca
- Python
Adopt for
- Aquila2
- Official suite for Aquila2 series LLM by BAAI
- 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.
Persona
- Aquila2
- -
- Chinese-LLaMA-Alpaca
- -
Runtime
- Aquila2
- -
- Chinese-LLaMA-Alpaca
- -
License
- Aquila2
- (unknown)
- Chinese-LLaMA-Alpaca
- The tool is licensed under Apache-2.0, allowing for free use, modification, and distribution.
Last pushed
- Aquila2
- Oct 11, 2024
- Chinese-LLaMA-Alpaca
- Apr 19, 2026
Categories
- Aquila2
- Inference & Serving, LLM Frameworks, Model Training
- Chinese-LLaMA-Alpaca
- Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- Aquila2
- Dormant (18%)
- Chinese-LLaMA-Alpaca
- Slowing (36%)
Days since push
- Aquila2
- 708d
- Chinese-LLaMA-Alpaca
- 152d
Open issues (now)
- Aquila2
- 2
- Chinese-LLaMA-Alpaca
- 5
Stars delta
- Aquila2
- -1 (30d)
- Chinese-LLaMA-Alpaca
- +10 (30d)
Open issues delta
- Aquila2
- 0 (30d)
- Chinese-LLaMA-Alpaca
- -1 (30d)
Owner type
- Aquila2
- Organization
- Chinese-LLaMA-Alpaca
- User
OSV dependency advisories
- Aquila2
- No lockfile (source not queried)
- Chinese-LLaMA-Alpaca
- Published findings
Full report
- Aquila2
- Trust report
- Chinese-LLaMA-Alpaca
- Trust report
Choose Aquila2 if…
- Tags unique to Aquila2: llm-inference, llm-training.
- Need specialized support from Beijing Academy of Artificial Intelligence
- Leaner open-issue backlog (2).
When NOT to use Aquila2
- Require comprehensive API and documentation clarity
- Preferring open source licensing details
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, lora, nlp.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (FlagAI-Open/Aquila2) · observed Sep 20, 2026
- GitHub forks (FlagAI-Open/Aquila2) · observed Sep 20, 2026
- Last push (FlagAI-Open/Aquila2) · observed Oct 11, 2024
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: Aquila2 445 · Chinese-LLaMA-Alpaca 19k (synced Sep 20, 2026).
Common questions
- What is the difference between Aquila2 and Chinese-LLaMA-Alpaca?
- Aquila2: Official repository for Aquila2 series large language models by BAAI. Chinese-LLaMA-Alpaca: Chinese LLaMA & Alpaca LLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose Aquila2 over Chinese-LLaMA-Alpaca?
- Choose Aquila2 over Chinese-LLaMA-Alpaca when Tags unique to Aquila2: llm-inference, llm-training; Need specialized support from Beijing Academy of Artificial Intelligence; Leaner open-issue backlog (2).
- When should I choose Chinese-LLaMA-Alpaca over Aquila2?
- Choose Chinese-LLaMA-Alpaca over Aquila2 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, lora, nlp; When you need Chinese-specific large language models for tasks that require deep understanding of the Chinese language.
- When should I avoid Aquila2?
- Require comprehensive API and documentation clarity Preferring open source licensing details
- 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.
- Is Aquila2 or Chinese-LLaMA-Alpaca more popular on GitHub?
- Chinese-LLaMA-Alpaca has more GitHub stars (18,943 vs 445). Stars measure visibility, not whether either tool fits your constraints.
- Are Aquila2 and Chinese-LLaMA-Alpaca open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Aquila2 or Chinese-LLaMA-Alpaca?
- GraphCanon lists graph-backed alternatives at Aquila2 alternatives and Chinese-LLaMA-Alpaca alternatives (Aquila2 markdown twin, Chinese-LLaMA-Alpaca 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, Aquila2 or Chinese-LLaMA-Alpaca?
- Aquila2: Dormant. Chinese-LLaMA-Alpaca: 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 Aquila2 and Chinese-LLaMA-Alpaca?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Aquila2 trust report; Chinese-LLaMA-Alpaca trust report.