Comparison
Awesome-Chinese-LLM vs pai
Verdict
Pick Awesome-Chinese-LLM when tags unique to Awesome-Chinese-LLM: awesome-lists, llama, chinese, llm; pick pai when tags unique to pai: gpu, cluster-manager, ai, artificial-intelligence.
Markdown twin · Awesome-Chinese-LLM alternatives · pai alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | Awesome-Chinese-LLM | pai |
|---|---|---|
| Maintenance | Steady (62d since push) As of today · github_public_v1 | Archived (765d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- Awesome-Chinese-LLM
- 整理开源的中文大语言模型
- pai
- Resource scheduling and cluster management for AI
Stars
- Awesome-Chinese-LLM
- 23k
- pai
- 2.7k
Forks
- Awesome-Chinese-LLM
- 2.1k
- pai
- 549
Open issues
- Awesome-Chinese-LLM
- 23
- pai
- 282
Language
- Awesome-Chinese-LLM
- -
- pai
- JavaScript
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.
- pai
- -
Persona
- Awesome-Chinese-LLM
- -
- pai
- -
Runtime
- Awesome-Chinese-LLM
- -
- pai
- -
License
- Awesome-Chinese-LLM
- -
- pai
- MIT
Last pushed
- Awesome-Chinese-LLM
- May 10, 2026
- pai
- Jun 6, 2024
Categories
- Awesome-Chinese-LLM
- Model Training, LLM Frameworks
- pai
- Model Training
Trust and health
Maintenance
- Awesome-Chinese-LLM
- Steady (60%)
- pai
- Archived (8%)
Days since push
- Awesome-Chinese-LLM
- 62d
- pai
- 765d
Archived on GitHub
- Awesome-Chinese-LLM
- No
- pai
- Yes
Open issues (now)
- Awesome-Chinese-LLM
- 23
- pai
- 282
Owner type
- Awesome-Chinese-LLM
- User
- pai
- Organization
Full report
- Awesome-Chinese-LLM
- Trust report
- pai
- Trust report
Choose Awesome-Chinese-LLM if…
- Tags unique to Awesome-Chinese-LLM: awesome-lists, llama, chinese, llm.
- Also covers LLM Frameworks.
- 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 pai if…
- Tags unique to pai: gpu, cluster-manager, ai, artificial-intelligence.
When NOT to use pai
- pai is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
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 Jul 11, 2026
- GitHub forks (AiHubCN/Awesome-Chinese-LLM) · observed Jul 11, 2026
- Last push (AiHubCN/Awesome-Chinese-LLM) · observed May 10, 2026
- License file (unknown) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (microsoft/pai) · observed Jul 11, 2026
- GitHub forks (microsoft/pai) · observed Jul 11, 2026
- Last push (microsoft/pai) · observed Jun 6, 2024
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Awesome-Chinese-LLM 23k · pai 2.7k (synced Jul 11, 2026).
Common questions
- What is the difference between Awesome-Chinese-LLM and pai?
- Awesome-Chinese-LLM: 整理开源的中文大语言模型. pai: Resource scheduling and cluster management for AI. See the comparison table for live GitHub stats and shared categories.
- When should I choose Awesome-Chinese-LLM over pai?
- Choose Awesome-Chinese-LLM over pai when Tags unique to Awesome-Chinese-LLM: awesome-lists, llama, chinese, llm; Also covers LLM Frameworks; If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately.
- When should I choose pai over Awesome-Chinese-LLM?
- Choose pai over Awesome-Chinese-LLM when Tags unique to pai: gpu, cluster-manager, ai, artificial-intelligence.
- 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 pai?
- pai is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is Awesome-Chinese-LLM or pai more popular on GitHub?
- Awesome-Chinese-LLM has more GitHub stars (22,670 vs 2,683). Stars measure visibility, not whether either tool fits your constraints.
- Are Awesome-Chinese-LLM and pai open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Awesome-Chinese-LLM or pai?
- GraphCanon lists graph-backed alternatives at Awesome-Chinese-LLM alternatives and pai alternatives (Awesome-Chinese-LLM markdown twin, pai 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 pai?
- Awesome-Chinese-LLM: Steady. pai: Archived. 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 pai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-Chinese-LLM trust report; pai trust report.