--- title: "distilabel vs awesome-chatgpt-prompts-zh" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/argilla-io-distilabel-vs-plexpt-awesome-chatgpt-prompts-zh" tools: ["argilla-io-distilabel", "plexpt-awesome-chatgpt-prompts-zh"] --- # distilabel vs awesome-chatgpt-prompts-zh *GraphCanon updated Jul 12, 2026* ## Verdict Pick distilabel when license: distilabel is Apache-2.0, awesome-chatgpt-prompts-zh is MIT; pick awesome-chatgpt-prompts-zh when license: awesome-chatgpt-prompts-zh is MIT, distilabel is Apache-2.0. [distilabel](https://distilabel.argilla.io) reports 3.3k GitHub stars, 247 forks, and 99 open issues, last pushed Jun 29, 2026. [awesome-chatgpt-prompts-zh](https://chat.aimakex.com/) has 61k stars, 14k forks, and 46 open issues, last pushed Apr 28, 2026. Figures are from public GitHub metadata via [distilabel's repository](https://github.com/argilla-io/distilabel) and [awesome-chatgpt-prompts-zh's repository](https://github.com/PlexPt/awesome-chatgpt-prompts-zh). | | [distilabel](/tools/argilla-io-distilabel.md) | [awesome-chatgpt-prompts-zh](/tools/plexpt-awesome-chatgpt-prompts-zh.md) | | --- | --- | --- | | Tagline | Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers. | ChatGPT 中文调教指南 | | Stars | 3,319 | 60,907 | | Forks | 247 | 13,548 | | Open issues | 99 | 46 | | Language | Python | - | | Adopt for | - | awesome-chatgpt-prompts-zh 是一个针对 ChatGPT 的中文使用指南和提示集合，旨在帮助用户更好地利用这个语言模型完成多样的任务和场景。 | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, Data & Retrieval | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [distilabel](/tools/argilla-io-distilabel.md) | [awesome-chatgpt-prompts-zh](/tools/plexpt-awesome-chatgpt-prompts-zh.md) | | --- | --- | --- | | Maintenance | Active (82%) | Steady (60%) | | Days since push | 12d | 73d | | Open issues (now) | 99 | 46 | | Owner type | Organization | User | | Full report | [trust report](/tools/argilla-io-distilabel/trust.md) | [trust report](/tools/plexpt-awesome-chatgpt-prompts-zh/trust.md) | ## Shared compatibility - **Python**: [distilabel](/tools/argilla-io-distilabel.md) - Python runtime; [awesome-chatgpt-prompts-zh](/tools/plexpt-awesome-chatgpt-prompts-zh.md) - Python runtime ## Decision facts: awesome-chatgpt-prompts-zh - **Pricing:** unknown - **Requirements:** 此工具主要是关于如何使用ChatGPT进行中文场景下的各种任务，并不是一个独立的服务或框架，用户需要自行准备ChatGPT的访问和使用环境。 - **Adopt for:** awesome-chatgpt-prompts-zh 是一个针对 ChatGPT 的中文使用指南和提示集合，旨在帮助用户更好地利用这个语言模型完成多样的任务和场景。 ## Choose when ### Choose distilabel if… - License: distilabel is Apache-2.0, awesome-chatgpt-prompts-zh is MIT. - Tags unique to distilabel: llms, synthetic-data, ai, rlhf. - Also covers Data & Retrieval. ### Choose awesome-chatgpt-prompts-zh if… - License: awesome-chatgpt-prompts-zh is MIT, distilabel is Apache-2.0. - Requirements: 此工具主要是关于如何使用ChatGPT进行中文场景下的各种任务，并不是一个独立的服务或框架，用户需要自行准备ChatGPT的访问和使用环境。. - Tags unique to awesome-chatgpt-prompts-zh: chat-gpt, chatgpt, gpt, chatgpt4. - 当您需要指导如何优化您的中文输入以获得更好的回应时； ## When NOT to use distilabel - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ## When NOT to use awesome-chatgpt-prompts-zh - 如果需要严格的本地法律法规专业知识指导，因为它可能缺乏针对具体国家和地区的深度定制化法律服务； - 对于实时性和高度专业化的技术问题解答需求较少优化，因为它主要为文本创作提供支持和技术性的输入提示指南。 ## Common questions ### What is the difference between distilabel and awesome-chatgpt-prompts-zh? distilabel: Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.. awesome-chatgpt-prompts-zh: ChatGPT 中文调教指南. See the comparison table for live GitHub stats and shared categories. ### When should I choose distilabel over awesome-chatgpt-prompts-zh? Choose distilabel over awesome-chatgpt-prompts-zh when License: distilabel is Apache-2.0, awesome-chatgpt-prompts-zh is MIT; Tags unique to distilabel: llms, synthetic-data, ai, rlhf; Also covers Data & Retrieval. ### When should I choose awesome-chatgpt-prompts-zh over distilabel? Choose awesome-chatgpt-prompts-zh over distilabel when License: awesome-chatgpt-prompts-zh is MIT, distilabel is Apache-2.0; Requirements: 此工具主要是关于如何使用ChatGPT进行中文场景下的各种任务，并不是一个独立的服务或框架，用户需要自行准备ChatGPT的访问和使用环境。; Tags unique to awesome-chatgpt-prompts-zh: chat-gpt, chatgpt, gpt, chatgpt4; 当您需要指导如何优化您的中文输入以获得更好的回应时；. ### When should I avoid distilabel? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ### When should I avoid awesome-chatgpt-prompts-zh? 如果需要严格的本地法律法规专业知识指导，因为它可能缺乏针对具体国家和地区的深度定制化法律服务； 对于实时性和高度专业化的技术问题解答需求较少优化，因为它主要为文本创作提供支持和技术性的输入提示指南。 ### Is distilabel or awesome-chatgpt-prompts-zh more popular on GitHub? awesome-chatgpt-prompts-zh has more GitHub stars (60,907 vs 3,319). Stars measure visibility, not whether either tool fits your constraints. ### Are distilabel and awesome-chatgpt-prompts-zh open source? Yes - both are open-source projects on GitHub (distilabel: Apache-2.0, awesome-chatgpt-prompts-zh: MIT). ### Where can I find alternatives to distilabel or awesome-chatgpt-prompts-zh? GraphCanon lists graph-backed alternatives at [distilabel alternatives](/tools/argilla-io-distilabel/alternatives) and [awesome-chatgpt-prompts-zh alternatives](/tools/plexpt-awesome-chatgpt-prompts-zh/alternatives) ([distilabel markdown twin](/tools/argilla-io-distilabel/alternatives.md), [awesome-chatgpt-prompts-zh markdown twin](/tools/plexpt-awesome-chatgpt-prompts-zh/alternatives.md)), 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](/compare/argilla-io-distilabel-vs-plexpt-awesome-chatgpt-prompts-zh.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, distilabel or awesome-chatgpt-prompts-zh? distilabel: Active. awesome-chatgpt-prompts-zh: Steady. 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 distilabel and awesome-chatgpt-prompts-zh? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [distilabel trust report](/tools/argilla-io-distilabel/trust); [awesome-chatgpt-prompts-zh trust report](/tools/plexpt-awesome-chatgpt-prompts-zh/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=argilla-io-distilabel`](/api/graphcanon/graph?tool=argilla-io-distilabel) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_