--- title: "awesome-gpt3 vs Awesome-Prompt-Engineering" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/elyase-awesome-gpt3-vs-promptslab-awesome-prompt-engineering" tools: ["elyase-awesome-gpt3", "promptslab-awesome-prompt-engineering"] --- # awesome-gpt3 vs Awesome-Prompt-Engineering *GraphCanon updated Aug 6, 2026* ## Verdict Pick awesome-gpt3 if awesome-gpt3 is a curated collection of demonstrations and articles illustrating the capabilities of GPT-3 in various domains such as app design, data analysis, programming, and text generation; pick Awesome-Prompt-Engineering if awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. [awesome-gpt3](https://github.com/elyase/awesome-gpt3) reports 4.5k GitHub stars, 345 forks, and 26 open issues, last pushed Aug 27, 2023. [Awesome-Prompt-Engineering](https://discord.gg/m88xfYMbK6) has 6.2k stars, 734 forks, and 94 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [awesome-gpt3's repository](https://github.com/elyase/awesome-gpt3) and [Awesome-Prompt-Engineering's repository](https://github.com/promptslab/Awesome-Prompt-Engineering). | | [awesome-gpt3](/tools/elyase-awesome-gpt3.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Tagline | A collection of demos and articles about the OpenAI GPT-3 API | Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers | | Stars | 4,520 | 6,197 | | Forks | 345 | 734 | | Open issues | 26 | 94 | | Language | - | TypeScript | | Adopt for | awesome-gpt3 is a curated collection of demonstrations and articles illustrating the capabilities of GPT-3 in various domains such as app design, data analysis, programming, and text generation. | Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | License information not specified, therefore usage rights are uncertain. | Apache-2.0 | | Categories | Model Training | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-gpt3](/tools/elyase-awesome-gpt3.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Very active (96%) | | Days since push | 1075d | 0d | | Archived on GitHub | Yes | No | | Open issues (now) | 26 | 94 | | Owner type | User | Organization | | Full report | [trust report](/tools/elyase-awesome-gpt3/trust.md) | [trust report](/tools/promptslab-awesome-prompt-engineering/trust.md) | ## Shared compatibility - **Python**: [awesome-gpt3](/tools/elyase-awesome-gpt3.md) - Python runtime; [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) - Python runtime ## Decision facts: awesome-gpt3 - **Requirements:** - No specific technical requirements stated except for engaging with GPT-3 through its API. - **Adopt for:** awesome-gpt3 is a curated collection of demonstrations and articles illustrating the capabilities of GPT-3 in various domains such as app design, data analysis, programming, and text generation. - **License detail:** License information not specified, therefore usage rights are uncertain. ## Decision facts: Awesome-Prompt-Engineering - **Adopt for:** Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. ## Choose when ### Choose awesome-gpt3 if… - Requirements: - No specific technical requirements stated except for engaging with GPT-3 through its API.. - Tags unique to awesome-gpt3: ai demos, gpt-3 applications. - - When you are looking for specific examples of how to leverage GPT-3's powerful API across different applications ranging from code generation to creative writing. ### Choose Awesome-Prompt-Engineering if… - Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, gpt. - Also covers Developer Tools. - You need focused materials on GPT and related models for prompt engineering ## When NOT to use awesome-gpt3 - - When seeking a direct development tool to integrate GPT-3 into your projects without further curation and customization. 'awesome-gpt3' is an example showcase rather than an SDK. - - If you require specific implementations for certain tasks like SEO optimization or language-specific translation beyond the provided samples, as it mainly contains links to tweets and external sites ## When NOT to use Awesome-Prompt-Engineering - The project requires languages other than TypeScript - Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering ## Common questions ### What is the difference between awesome-gpt3 and Awesome-Prompt-Engineering? awesome-gpt3: A collection of demos and articles about the OpenAI GPT-3 API. Awesome-Prompt-Engineering: Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-gpt3 over Awesome-Prompt-Engineering? Choose awesome-gpt3 over Awesome-Prompt-Engineering when Requirements: - No specific technical requirements stated except for engaging with GPT-3 through its API.; Tags unique to awesome-gpt3: ai demos, gpt-3 applications; - When you are looking for specific examples of how to leverage GPT-3's powerful API across different applications ranging from code generation to creative writing. ### When should I choose Awesome-Prompt-Engineering over awesome-gpt3? Choose Awesome-Prompt-Engineering over awesome-gpt3 when Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, gpt; Also covers Developer Tools; You need focused materials on GPT and related models for prompt engineering. ### When should I avoid awesome-gpt3? - When seeking a direct development tool to integrate GPT-3 into your projects without further curation and customization. 'awesome-gpt3' is an example showcase rather than an SDK. - If you require specific implementations for certain tasks like SEO optimization or language-specific translation beyond the provided samples, as it mainly contains links to tweets and external sites ### When should I avoid Awesome-Prompt-Engineering? The project requires languages other than TypeScript Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering ### Is awesome-gpt3 or Awesome-Prompt-Engineering more popular on GitHub? Awesome-Prompt-Engineering has more GitHub stars (6,197 vs 4,520). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-gpt3 and Awesome-Prompt-Engineering open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-gpt3 or Awesome-Prompt-Engineering? GraphCanon lists graph-backed alternatives at [awesome-gpt3 alternatives](/tools/elyase-awesome-gpt3/alternatives) and [Awesome-Prompt-Engineering alternatives](/tools/promptslab-awesome-prompt-engineering/alternatives) ([awesome-gpt3 markdown twin](/tools/elyase-awesome-gpt3/alternatives.md), [Awesome-Prompt-Engineering markdown twin](/tools/promptslab-awesome-prompt-engineering/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/elyase-awesome-gpt3-vs-promptslab-awesome-prompt-engineering.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-gpt3 or Awesome-Prompt-Engineering? awesome-gpt3: Archived. Awesome-Prompt-Engineering: Very active. 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-gpt3 and Awesome-Prompt-Engineering? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-gpt3 trust report](/tools/elyase-awesome-gpt3/trust); [Awesome-Prompt-Engineering trust report](/tools/promptslab-awesome-prompt-engineering/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=elyase-awesome-gpt3`](/api/graphcanon/graph?tool=elyase-awesome-gpt3) - 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/_