--- title: "DeepSeek-R1 vs awesome-gpt3" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deepseek-ai-deepseek-r1-vs-elyase-awesome-gpt3" tools: ["deepseek-ai-deepseek-r1", "elyase-awesome-gpt3"] --- # DeepSeek-R1 vs awesome-gpt3 *GraphCanon updated Jul 12, 2026* ## Verdict Pick DeepSeek-R1 if deepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use; 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. [DeepSeek-R1](https://github.com/deepseek-ai/DeepSeek-R1) reports 92k GitHub stars, 12k forks, and 45 open issues, last pushed Jun 27, 2025. [awesome-gpt3](https://github.com/elyase/awesome-gpt3) has 4.5k stars, 347 forks, and 26 open issues, last pushed Aug 27, 2023. Figures are from public GitHub metadata via [DeepSeek-R1's repository](https://github.com/deepseek-ai/DeepSeek-R1) and [awesome-gpt3's repository](https://github.com/elyase/awesome-gpt3). | | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | [awesome-gpt3](/tools/elyase-awesome-gpt3.md) | | --- | --- | --- | | Tagline | Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses. | A collection of demos and articles about the OpenAI GPT-3 API | | Stars | 91,991 | 4,525 | | Forks | 11,711 | 347 | | Open issues | 45 | 26 | | Language | - | - | | Adopt for | DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. | 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. | | Persona | - | - | | Runtime | - | - | | License | MIT | License information not specified, therefore usage rights are uncertain. | | Categories | LLM Frameworks, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | [awesome-gpt3](/tools/elyase-awesome-gpt3.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Archived (8%) | | Days since push | 379d | 1048d | | Archived on GitHub | No | Yes | | Open issues (now) | 45 | 26 | | Owner type | Organization | User | | Full report | [trust report](/tools/deepseek-ai-deepseek-r1/trust.md) | [trust report](/tools/elyase-awesome-gpt3/trust.md) | ## Decision facts: DeepSeek-R1 - **Pricing:** freemium - The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository. - **Requirements:** Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs. - **Adopt for:** DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. ## 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. ## Choose when ### Choose DeepSeek-R1 if… - Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.. - Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.. - Tags unique to DeepSeek-R1: derived models, mit license, distilled models, commercial use. - Also covers LLM Frameworks. - When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics. ### Choose awesome-gpt3 if… - Requirements: - No specific technical requirements stated except for engaging with GPT-3 through its API.. - Tags unique to awesome-gpt3: gpt-3 applications, ai demos. - - 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 NOT to use DeepSeek-R1 - Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. - If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series. ## 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 ## Common questions ### What is the difference between DeepSeek-R1 and awesome-gpt3? DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. awesome-gpt3: A collection of demos and articles about the OpenAI GPT-3 API. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepSeek-R1 over awesome-gpt3? Choose DeepSeek-R1 over awesome-gpt3 when Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.; Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.; Tags unique to DeepSeek-R1: derived models, mit license, distilled models, commercial use; Also covers LLM Frameworks; When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics. ### When should I choose awesome-gpt3 over DeepSeek-R1? Choose awesome-gpt3 over DeepSeek-R1 when Requirements: - No specific technical requirements stated except for engaging with GPT-3 through its API.; Tags unique to awesome-gpt3: gpt-3 applications, ai demos; - 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 avoid DeepSeek-R1? Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series. ### 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 ### Is DeepSeek-R1 or awesome-gpt3 more popular on GitHub? DeepSeek-R1 has more GitHub stars (91,991 vs 4,525). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepSeek-R1 and awesome-gpt3 open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to DeepSeek-R1 or awesome-gpt3? GraphCanon lists graph-backed alternatives at [DeepSeek-R1 alternatives](/tools/deepseek-ai-deepseek-r1/alternatives) and [awesome-gpt3 alternatives](/tools/elyase-awesome-gpt3/alternatives) ([DeepSeek-R1 markdown twin](/tools/deepseek-ai-deepseek-r1/alternatives.md), [awesome-gpt3 markdown twin](/tools/elyase-awesome-gpt3/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/deepseek-ai-deepseek-r1-vs-elyase-awesome-gpt3.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepSeek-R1 or awesome-gpt3? DeepSeek-R1: Dormant. awesome-gpt3: 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 DeepSeek-R1 and awesome-gpt3? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepSeek-R1 trust report](/tools/deepseek-ai-deepseek-r1/trust); [awesome-gpt3 trust report](/tools/elyase-awesome-gpt3/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=deepseek-ai-deepseek-r1`](/api/graphcanon/graph?tool=deepseek-ai-deepseek-r1) - 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/_