Comparison
Awesome-Chinese-LLM vs oneflow
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 oneflow if oneFlow is a deep learning framework built for user-friendly, scalable, and efficient performance in model training, with support via CUDA installations.
Markdown twin · Awesome-Chinese-LLM alternatives · oneflow alternatives
GraphCanon updated 1w
Trust & integrity
| Signal | Awesome-Chinese-LLM | oneflow |
|---|---|---|
| Maintenance | Slowing (98d since push) As of 1w · github_public_v1 | Slowing (242d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) 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
- oneflow
- OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
Stars
- Awesome-Chinese-LLM
- 23k
- oneflow
- 9.4k
Forks
- Awesome-Chinese-LLM
- 2.1k
- oneflow
- 1.0k
Open issues
- Awesome-Chinese-LLM
- 27
- oneflow
- 644
Language
- Awesome-Chinese-LLM
- -
- oneflow
- C++
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.
- oneflow
- OneFlow is a deep learning framework built for user-friendly, scalable, and efficient performance in model training, with support via CUDA installations.
Persona
- Awesome-Chinese-LLM
- -
- oneflow
- -
Runtime
- Awesome-Chinese-LLM
- -
- oneflow
- -
License
- Awesome-Chinese-LLM
- -
- oneflow
- Apache-2.0
Last pushed
- Awesome-Chinese-LLM
- May 10, 2026
- oneflow
- Dec 4, 2025
Categories
- Awesome-Chinese-LLM
- LLM Frameworks, Model Training
- oneflow
- Model Training
Trust and health
Days since push
- Awesome-Chinese-LLM
- 98d
- oneflow
- 242d
Open issues (now)
- Awesome-Chinese-LLM
- 27
- oneflow
- 644
Stars delta
- Awesome-Chinese-LLM
- +53 (30d)
- oneflow
- Unknown
Open issues delta
- Awesome-Chinese-LLM
- +3 (30d)
- oneflow
- Unknown
Owner type
- Awesome-Chinese-LLM
- User
- oneflow
- Organization
Full report
- Awesome-Chinese-LLM
- Trust report
- oneflow
- Trust report
Choose Awesome-Chinese-LLM if…
- Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese, llama.
- 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 oneflow if…
- Tags unique to oneflow: cuda, deep-learning, distributed, machine-learning.
- OneFlow is preferable when you need a user-friendly framework for both CPU and CUDA installations, aiming to streamline the deep learning workflow.
When NOT to use oneflow
- Avoid OneFlow if your project requires extensive customization features not natively supported, as switching to another framework might offer better flexibility.
- If the development environment lacks support for CUDA or Python3-based installation methods, consider an alternative framework that suits your hardware and software environment more closely.
- OneFlow may not be ideal when working in regions with difficulty accessing external libraries due to dependency management tailored towards certain geographic locations.
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 (Oneflow-Inc/oneflow) · observed Aug 3, 2026
- GitHub forks (Oneflow-Inc/oneflow) · observed Aug 3, 2026
- Last push (Oneflow-Inc/oneflow) · observed Dec 4, 2025
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Awesome-Chinese-LLM 23k · oneflow 9.4k (synced Aug 17, 2026).
Common questions
- What is the difference between Awesome-Chinese-LLM and oneflow?
- Awesome-Chinese-LLM: 整理开源的中文大语言模型. oneflow: OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.. See the comparison table for live GitHub stats and shared categories.
- When should I choose Awesome-Chinese-LLM over oneflow?
- Choose Awesome-Chinese-LLM over oneflow when Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese, llama; 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 oneflow over Awesome-Chinese-LLM?
- Choose oneflow over Awesome-Chinese-LLM when Tags unique to oneflow: cuda, deep-learning, distributed, machine-learning; OneFlow is preferable when you need a user-friendly framework for both CPU and CUDA installations, aiming to streamline the deep learning workflow.
- 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 oneflow?
- Avoid OneFlow if your project requires extensive customization features not natively supported, as switching to another framework might offer better flexibility. If the development environment lacks support for CUDA or Python3-based installation methods, consider an alternative framework that suits your hardware and software environment more closely. OneFlow may not be ideal when working in regions with difficulty accessing external libraries due to dependency management tailored towards certain geographic locations.
- Is Awesome-Chinese-LLM or oneflow more popular on GitHub?
- Awesome-Chinese-LLM has more GitHub stars (22,738 vs 9,420). Stars measure visibility, not whether either tool fits your constraints.
- Are Awesome-Chinese-LLM and oneflow open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Awesome-Chinese-LLM or oneflow?
- GraphCanon lists graph-backed alternatives at Awesome-Chinese-LLM alternatives and oneflow alternatives (Awesome-Chinese-LLM markdown twin, oneflow 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 oneflow?
- Awesome-Chinese-LLM: Slowing. oneflow: 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 oneflow?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-Chinese-LLM trust report; oneflow trust report.