--- title: "LlamaFactory vs dart-math" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-hkust-nlp-dart-math" tools: ["hiyouga-llamafactory", "hkust-nlp-dart-math"] --- # LlamaFactory vs dart-math *GraphCanon updated Jul 11, 2026* ## Verdict Pick LlamaFactory when llamaFactory is primarily Python; dart-math is Jupyter Notebook; pick dart-math when dart-math is primarily Jupyter Notebook; LlamaFactory is Python. [LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [dart-math](https://hkust-nlp.github.io/dart-math/) has 120 stars, 8 forks, and 5 open issues, last pushed Dec 10, 2024. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [dart-math's repository](https://github.com/hkust-nlp/dart-math). | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [dart-math](/tools/hkust-nlp-dart-math.md) | | --- | --- | --- | | Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | [NeurIPS'24] Official code for *🎯DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving* | | Stars | 73,157 | 120 | | Forks | 8,937 | 8 | | Open issues | 1,067 | 5 | | Language | Python | Jupyter Notebook | | Adopt for | LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [dart-math](/tools/hkust-nlp-dart-math.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 578d | | Open issues (now) | 1.1k | 5 | | Owner type | User | Organization | | Security scan | No lockfile | No criticals | | Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/hkust-nlp-dart-math/trust.md) | ## Decision facts: LlamaFactory - **Adopt for:** LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization. ## Choose when ### Choose LlamaFactory if… - LlamaFactory is primarily Python; dart-math is Jupyter Notebook. - License: LlamaFactory is Apache-2.0, dart-math is MIT. - Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### Choose dart-math if… - dart-math is primarily Jupyter Notebook; LlamaFactory is Python. - License: dart-math is MIT, LlamaFactory is Apache-2.0. - Tags unique to dart-math: deep-learning, llm, nlp, jupyter notebook. - Also covers Inference & Serving. ## When NOT to use LlamaFactory - When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. - If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa ## When NOT to use dart-math - Last GitHub push was 579 days ago (dormant maintenance, Dec 10, 2024). Validate activity before betting a new project on dart-math. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between LlamaFactory and dart-math? LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. dart-math: [NeurIPS'24] Official code for *🎯DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving*. See the comparison table for live GitHub stats and shared categories. ### When should I choose LlamaFactory over dart-math? Choose LlamaFactory over dart-math when LlamaFactory is primarily Python; dart-math is Jupyter Notebook; License: LlamaFactory is Apache-2.0, dart-math is MIT; Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### When should I choose dart-math over LlamaFactory? Choose dart-math over LlamaFactory when dart-math is primarily Jupyter Notebook; LlamaFactory is Python; License: dart-math is MIT, LlamaFactory is Apache-2.0; Tags unique to dart-math: deep-learning, llm, nlp, jupyter notebook; Also covers Inference & Serving. ### When should I avoid LlamaFactory? When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa ### When should I avoid dart-math? Last GitHub push was 579 days ago (dormant maintenance, Dec 10, 2024). Validate activity before betting a new project on dart-math. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is LlamaFactory or dart-math more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 120). Stars measure visibility, not whether either tool fits your constraints. ### Are LlamaFactory and dart-math open source? Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, dart-math: MIT). ### Where can I find alternatives to LlamaFactory or dart-math? GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [dart-math alternatives](/tools/hkust-nlp-dart-math/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [dart-math markdown twin](/tools/hkust-nlp-dart-math/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/hiyouga-llamafactory-vs-hkust-nlp-dart-math.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LlamaFactory or dart-math? LlamaFactory: Very active. dart-math: 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 LlamaFactory and dart-math? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [dart-math trust report](/tools/hkust-nlp-dart-math/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hiyouga-llamafactory`](/api/graphcanon/graph?tool=hiyouga-llamafactory) - 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/_