Comparison
LlamaFactory vs Chinese-LLaMA-Alpaca
Verdict
Pick LlamaFactory if llamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization; pick Chinese-LLaMA-Alpaca if `Chinese-LLaMA-Alpaca` is a repository that includes Chinese versions of the LLaMA and Alpaca large language models, specifically designed with extended Chinese vocabulary and fine-tuned on Chinese instruction data.
Markdown twin · LlamaFactory alternatives · Chinese-LLaMA-Alpaca alternatives
GraphCanon updated 5d
vs
Trust & integrity
| Signal | LlamaFactory | Chinese-LLaMA-Alpaca |
|---|---|---|
| Maintenance | Very active (2d since push) As of 6d · github_public_v1 | Slowing (119d since push) As of 5d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 6d · github_public_v1 | Not a fork · Personal account As of 5d · 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
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
- Chinese-LLaMA-Alpaca
- Chinese LLaMA & Alpaca Large Language Models for Local CPU/GPU Training and Deployment
Stars
- LlamaFactory
- 74k
- Chinese-LLaMA-Alpaca
- 19k
Forks
- LlamaFactory
- 9.1k
- Chinese-LLaMA-Alpaca
- 1.8k
Open issues
- LlamaFactory
- 1.1k
- Chinese-LLaMA-Alpaca
- 6
Language
- LlamaFactory
- Python
- Chinese-LLaMA-Alpaca
- Python
Adopt for
- LlamaFactory
- LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.
- Chinese-LLaMA-Alpaca
- `Chinese-LLaMA-Alpaca` is a repository that includes Chinese versions of the LLaMA and Alpaca large language models, specifically designed with extended Chinese vocabulary and fine-tuned on Chinese instruction data for a
Persona
- LlamaFactory
- -
- Chinese-LLaMA-Alpaca
- -
Runtime
- LlamaFactory
- -
- Chinese-LLaMA-Alpaca
- -
License
- LlamaFactory
- Apache-2.0
- Chinese-LLaMA-Alpaca
- The repository is licensed under Apache-2.0 which allows you to use the content openly in both commercial and non-commercial projects provided you adhere to the licensing terms.
Last pushed
- LlamaFactory
- Aug 13, 2026
- Chinese-LLaMA-Alpaca
- Apr 19, 2026
Categories
- LlamaFactory
- LLM Frameworks, Model Training
- Chinese-LLaMA-Alpaca
- LLM Frameworks, Model Training
Trust and health
Maintenance
- LlamaFactory
- Very active (96%)
- Chinese-LLaMA-Alpaca
- Slowing (36%)
Days since push
- LlamaFactory
- 2d
- Chinese-LLaMA-Alpaca
- 119d
Open issues (now)
- LlamaFactory
- 1.1k
- Chinese-LLaMA-Alpaca
- 6
Stars delta
- LlamaFactory
- +803 (30d)
- Chinese-LLaMA-Alpaca
- -9 (30d)
Open issues delta
- LlamaFactory
- +39 (30d)
- Chinese-LLaMA-Alpaca
- 0 (30d)
OSV dependency advisories
- LlamaFactory
- No lockfile (source not queried)
- Chinese-LLaMA-Alpaca
- Published findings
Full report
- LlamaFactory
- Trust report
- Chinese-LLaMA-Alpaca
- Trust report
Typed relationship
LlamaFactory Chinese-LLaMA-Alpaca
Choose LlamaFactory if…
- Graph edge: LlamaFactory is a typed related of Chinese-LLaMA-Alpaca - see the relationship row above.
- Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning.
- When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
When NOT to use LlamaFactory
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory.
- If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
Choose Chinese-LLaMA-Alpaca if…
- Pricing: Access to `Chinese-LLaMA-Alpaca` models and documentation is free, but commercial usage should adhere to open-source licensing requirements..
- Graph edge: Chinese-LLaMA-Alpaca is a typed related of LlamaFactory - see the relationship row above.
- Tags unique to Chinese-LLaMA-Alpaca: alpaca, llama, nlp, pre-trained-language-models.
- You should consider using `Chinese-LLaMA-Alpaca` if your project involves local deployment and training using CPUs or GPUs, particularly if the focus is on Chinese language texts. These models are pre
When NOT to use Chinese-LLaMA-Alpaca
- `Chinese-LLaMA-Alpaca` might not be the best fit if your project requires extensive multi-language support beyond Chinese.
- If you are exclusively targeting markets where English is the primary language, and fine-tuning or additional pre-training on Chinese data does not add value to your application.
- Avoid using this tool if you require a model that has been extensively trained across global datasets for broad international comprehension, as `Chinese-LLaMA-Alpaca` is focused heavily on Chinese.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hiyouga/LlamaFactory) · observed Aug 16, 2026
- GitHub forks (hiyouga/LlamaFactory) · observed Aug 16, 2026
- Last push (hiyouga/LlamaFactory) · observed Aug 13, 2026
- License file (Apache-2.0) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ymcui/Chinese-LLaMA-Alpaca) · observed Aug 17, 2026
- GitHub forks (ymcui/Chinese-LLaMA-Alpaca) · observed Aug 17, 2026
- Last push (ymcui/Chinese-LLaMA-Alpaca) · observed Apr 19, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LlamaFactory 74k · Chinese-LLaMA-Alpaca 19k (synced Aug 16, 2026).
Common questions
- What is the difference between LlamaFactory and Chinese-LLaMA-Alpaca?
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. Chinese-LLaMA-Alpaca: Chinese LLaMA & Alpaca Large Language Models for Local CPU/GPU Training and Deployment. See the comparison table for live GitHub stats and shared categories.
- When should I choose LlamaFactory over Chinese-LLaMA-Alpaca?
- Choose LlamaFactory over Chinese-LLaMA-Alpaca when Graph edge: LlamaFactory is a typed related of Chinese-LLaMA-Alpaca - see the relationship row above; Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
- When should I choose Chinese-LLaMA-Alpaca over LlamaFactory?
- Choose Chinese-LLaMA-Alpaca over LlamaFactory when Pricing: Access to
Chinese-LLaMA-Alpacamodels and documentation is free, but commercial usage should adhere to open-source licensing requirements.; Graph edge: Chinese-LLaMA-Alpaca is a typed related of LlamaFactory - see the relationship row above; Tags unique to Chinese-LLaMA-Alpaca: alpaca, llama, nlp, pre-trained-language-models; You should consider usingChinese-LLaMA-Alpacaif your project involves local deployment and training using CPUs or GPUs, particularly if the focus is on Chinese language texts. These models are pre. - When should I avoid LlamaFactory?
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
- When should I avoid Chinese-LLaMA-Alpaca?
Chinese-LLaMA-Alpacamight not be the best fit if your project requires extensive multi-language support beyond Chinese. If you are exclusively targeting markets where English is the primary language, and fine-tuning or additional pre-training on Chinese data does not add value to your application. Avoid using this tool if you require a model that has been extensively trained across global datasets for broad international comprehension, asChinese-LLaMA-Alpacais focused heavily on Chinese.- Is LlamaFactory or Chinese-LLaMA-Alpaca more popular on GitHub?
- LlamaFactory has more GitHub stars (74,132 vs 18,933). Stars measure visibility, not whether either tool fits your constraints.
- Are LlamaFactory and Chinese-LLaMA-Alpaca open source?
- Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, Chinese-LLaMA-Alpaca: Apache-2.0).
- Where can I find alternatives to LlamaFactory or Chinese-LLaMA-Alpaca?
- GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and Chinese-LLaMA-Alpaca alternatives (LlamaFactory 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, LlamaFactory or Chinese-LLaMA-Alpaca?
- LlamaFactory: Very active. 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 LlamaFactory and Chinese-LLaMA-Alpaca?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; Chinese-LLaMA-Alpaca trust report.