--- title: "DeepSeek-R1 vs huozi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deepseek-ai-deepseek-r1-vs-hit-scir-huozi" tools: ["deepseek-ai-deepseek-r1", "hit-scir-huozi"] --- # DeepSeek-R1 vs huozi *GraphCanon updated Aug 24, 2026* ## Verdict Pick DeepSeek-R1 if deepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use; pick huozi if huozi is a Python-based large model framework with Apache-2.0 license for fine-tuning and NLP applications. [DeepSeek-R1](https://github.com/deepseek-ai/DeepSeek-R1) reports 92k GitHub stars, 12k forks, and 38 open issues, last pushed Jun 27, 2025. [huozi](https://github.com/HIT-SCIR/huozi) has 393 stars, 26 forks, and 0 open issues, last pushed Sep 12, 2024. Figures are from public GitHub metadata via [DeepSeek-R1's repository](https://github.com/deepseek-ai/DeepSeek-R1) and [huozi's repository](https://github.com/HIT-SCIR/huozi). | | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | [huozi](/tools/hit-scir-huozi.md) | | --- | --- | --- | | Tagline | Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses. | General-purpose large model for fine-tuning and applications | | Stars | 91,982 | 393 | | Forks | 11,706 | 26 | | Open issues | 38 | 0 | | Language | - | Python | | Adopt for | DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. | Huozi is a Python-based large model framework with Apache-2.0 license for fine-tuning and NLP applications. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | [huozi](/tools/hit-scir-huozi.md) | | --- | --- | --- | | Days since push | 405d | 711d | | Open issues (now) | 38 | 0 | | Stars delta | Unknown | -2 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/deepseek-ai-deepseek-r1/trust.md) | [trust report](/tools/hit-scir-huozi/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: huozi - **Adopt for:** Huozi is a Python-based large model framework with Apache-2.0 license for fine-tuning and NLP applications. ## Choose when ### Choose DeepSeek-R1 if… - License: DeepSeek-R1 is MIT, huozi is Apache-2.0. - 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: commercial use, derived models, distilled models, mit-license. - 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 huozi if… - License: huozi is Apache-2.0, DeepSeek-R1 is MIT. - Tags unique to huozi: fine-tuning, large language models, llm, nlp. - When working on projects that require fast integration of pre-trained language models through its streamlined fine-tuning capabilities. ## 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 huozi - If your project requires proprietary licensing, as Huozi is under the Apache-2.0 license which may not meet all business models' requirements. - When needing a framework with comprehensive support for visual data or other non-textual machine learning applications. ## Common questions ### What is the difference between DeepSeek-R1 and huozi? DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. huozi: General-purpose large model for fine-tuning and applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepSeek-R1 over huozi? Choose DeepSeek-R1 over huozi when License: DeepSeek-R1 is MIT, huozi is Apache-2.0; 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: commercial use, derived models, distilled models, mit-license; 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 huozi over DeepSeek-R1? Choose huozi over DeepSeek-R1 when License: huozi is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to huozi: fine-tuning, large language models, llm, nlp; When working on projects that require fast integration of pre-trained language models through its streamlined fine-tuning capabilities. ### 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 huozi? If your project requires proprietary licensing, as Huozi is under the Apache-2.0 license which may not meet all business models' requirements. When needing a framework with comprehensive support for visual data or other non-textual machine learning applications. ### Is DeepSeek-R1 or huozi more popular on GitHub? DeepSeek-R1 has more GitHub stars (91,982 vs 393). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepSeek-R1 and huozi open source? Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, huozi: Apache-2.0). ### Where can I find alternatives to DeepSeek-R1 or huozi? GraphCanon lists graph-backed alternatives at [DeepSeek-R1 alternatives](/tools/deepseek-ai-deepseek-r1/alternatives) and [huozi alternatives](/tools/hit-scir-huozi/alternatives) ([DeepSeek-R1 markdown twin](/tools/deepseek-ai-deepseek-r1/alternatives.md), [huozi markdown twin](/tools/hit-scir-huozi/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-hit-scir-huozi.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepSeek-R1 or huozi? DeepSeek-R1: Dormant. huozi: 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 DeepSeek-R1 and huozi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepSeek-R1 trust report](/tools/deepseek-ai-deepseek-r1/trust); [huozi trust report](/tools/hit-scir-huozi/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/_