--- title: "promptsource vs awesome-gpt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bigscience-workshop-promptsource-vs-formulahendry-awesome-gpt" tools: ["bigscience-workshop-promptsource", "formulahendry-awesome-gpt"] --- # promptsource vs awesome-gpt *GraphCanon updated Aug 15, 2026* ## Verdict Pick promptsource if promptSource aids in creating, sharing, and using natural language prompts for large language models; pick awesome-gpt if awesome-gpt is a curated list of GPT and related resources, serving as a reference for developers exploring or working with large language models and their applications. [promptsource](https://github.com/bigscience-workshop/promptsource) reports 3.0k GitHub stars, 375 forks, and 43 open issues, last pushed Oct 23, 2023. [awesome-gpt](https://github.com/formulahendry/awesome-gpt) has 1.0k stars, 75 forks, and 27 open issues, last pushed May 29, 2024. Figures are from public GitHub metadata via [promptsource's repository](https://github.com/bigscience-workshop/promptsource) and [awesome-gpt's repository](https://github.com/formulahendry/awesome-gpt). | | [promptsource](/tools/bigscience-workshop-promptsource.md) | [awesome-gpt](/tools/formulahendry-awesome-gpt.md) | | --- | --- | --- | | Tagline | Toolkit for creating, sharing and using natural language prompts | Curated list of GPT and related resources | | Stars | 3,029 | 1,043 | | Forks | 375 | 75 | | Open issues | 43 | 27 | | Language | Python | - | | Adopt for | PromptSource aids in creating, sharing, and using natural language prompts for large language models. | awesome-gpt is a curated list of GPT and related resources, serving as a reference for developers exploring or working with large language models and their applications. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | - | | Categories | Developer Tools, Model Training | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [promptsource](/tools/bigscience-workshop-promptsource.md) | [awesome-gpt](/tools/formulahendry-awesome-gpt.md) | | --- | --- | --- | | Days since push | 1027d | 799d | | Open issues (now) | 43 | 27 | | Stars delta | +2 (30d) | Unknown | | Open issues delta | -1 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/bigscience-workshop-promptsource/trust.md) | [trust report](/tools/formulahendry-awesome-gpt/trust.md) | ## Decision facts: promptsource - **Adopt for:** PromptSource aids in creating, sharing, and using natural language prompts for large language models. ## Decision facts: awesome-gpt - **Pricing:** unknown - Information about pricing is unavailable and likely does not apply as this is a curated list rather than a software service with licensing costs. - **Requirements:** Since awesome-gpt is an informational repository, it itself does not have RAM requirements or Docker needs. However, users might require internet access to view - **Adopt for:** awesome-gpt is a curated list of GPT and related resources, serving as a reference for developers exploring or working with large language models and their applications. ## Choose when ### Choose promptsource if… - Tags unique to promptsource: few-shot, fine-tuning, language-models, machine-learning. - Also covers Model Training. - When you need to create reusable prompts for multiple datasets with a focus on simplicity through a templating language called Jinja. ### Choose awesome-gpt if… - Pricing: Information about pricing is unavailable and likely does not apply as this is a curated list rather than a software service with licensing costs.. - Requirements: Since awesome-gpt is an informational repository, it itself does not have RAM requirements or Docker needs. However, users might require internet access to view. - Tags unique to awesome-gpt: chatgpt, gpt, llm, openai. - Also covers LLM Frameworks. - Use awesome-gpt if you are looking for a comprehensive collection of links and resources specifically focused on GPT, ChatGPT, OpenAI products, and other large-scale AI tools. ## When NOT to use promptsource - Avoid if you require complex prompt customization beyond what simple templating can offer, as PromptSource is not designed for intricate configurations. - Not suitable for users focused on real-time interaction with prompts, since it lacks dynamic features for immediate adjustments. ## When NOT to use awesome-gpt - Avoid using awesome-gpt if you need detailed tutorials or in-depth technical documentation, as it primarily functions as an index of resources rather than an educational material provider. - Do not rely on awesome-gpt for real-time updates or specific usage statistics, tool availability, or pricing plans since the repository relies heavily on links external to its curation. ## Common questions ### What is the difference between promptsource and awesome-gpt? promptsource: Toolkit for creating, sharing and using natural language prompts. awesome-gpt: Curated list of GPT and related resources. See the comparison table for live GitHub stats and shared categories. ### When should I choose promptsource over awesome-gpt? Choose promptsource over awesome-gpt when Tags unique to promptsource: few-shot, fine-tuning, language-models, machine-learning; Also covers Model Training; When you need to create reusable prompts for multiple datasets with a focus on simplicity through a templating language called Jinja. ### When should I choose awesome-gpt over promptsource? Choose awesome-gpt over promptsource when Pricing: Information about pricing is unavailable and likely does not apply as this is a curated list rather than a software service with licensing costs.; Requirements: Since awesome-gpt is an informational repository, it itself does not have RAM requirements or Docker needs. However, users might require internet access to view; Tags unique to awesome-gpt: chatgpt, gpt, llm, openai; Also covers LLM Frameworks; Use awesome-gpt if you are looking for a comprehensive collection of links and resources specifically focused on GPT, ChatGPT, OpenAI products, and other large-scale AI tools. ### When should I avoid promptsource? Avoid if you require complex prompt customization beyond what simple templating can offer, as PromptSource is not designed for intricate configurations. Not suitable for users focused on real-time interaction with prompts, since it lacks dynamic features for immediate adjustments. ### When should I avoid awesome-gpt? Avoid using awesome-gpt if you need detailed tutorials or in-depth technical documentation, as it primarily functions as an index of resources rather than an educational material provider. Do not rely on awesome-gpt for real-time updates or specific usage statistics, tool availability, or pricing plans since the repository relies heavily on links external to its curation. ### Is promptsource or awesome-gpt more popular on GitHub? promptsource has more GitHub stars (3,029 vs 1,043). Stars measure visibility, not whether either tool fits your constraints. ### Are promptsource and awesome-gpt open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to promptsource or awesome-gpt? GraphCanon lists graph-backed alternatives at [promptsource alternatives](/tools/bigscience-workshop-promptsource/alternatives) and [awesome-gpt alternatives](/tools/formulahendry-awesome-gpt/alternatives) ([promptsource markdown twin](/tools/bigscience-workshop-promptsource/alternatives.md), [awesome-gpt markdown twin](/tools/formulahendry-awesome-gpt/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/bigscience-workshop-promptsource-vs-formulahendry-awesome-gpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, promptsource or awesome-gpt? promptsource: Dormant. awesome-gpt: Dormant. 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 promptsource and awesome-gpt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [promptsource trust report](/tools/bigscience-workshop-promptsource/trust); [awesome-gpt trust report](/tools/formulahendry-awesome-gpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bigscience-workshop-promptsource`](/api/graphcanon/graph?tool=bigscience-workshop-promptsource) - 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/_