--- title: "LlamaFactory vs Chain-of-ThoughtsPapers" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-timothyxxx-chain-of-thoughtspapers" tools: ["hiyouga-llamafactory", "timothyxxx-chain-of-thoughtspapers"] --- # LlamaFactory vs Chain-of-ThoughtsPapers *GraphCanon updated Jul 11, 2026* ## Verdict Pick LlamaFactory if 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; pick Chain-of-ThoughtsPapers if chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. [LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [Chain-of-ThoughtsPapers](https://github.com/Timothyxxx/Chain-of-ThoughtsPapers) has 2.1k stars, 142 forks, and 0 open issues, last pushed Oct 5, 2023. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [Chain-of-ThoughtsPapers's repository](https://github.com/Timothyxxx/Chain-of-ThoughtsPapers). | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [Chain-of-ThoughtsPapers](/tools/timothyxxx-chain-of-thoughtspapers.md) | | --- | --- | --- | | Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | A curated list of papers exploring chain-of-thought reasoning in large language models. | | Stars | 73,157 | 2,106 | | Forks | 8,937 | 142 | | Open issues | 1,067 | 0 | | Language | Python | - | | 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. | Chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. | | Persona | - | end user agent | | Runtime | - | - | | License | Apache-2.0 | - | | Categories | Model Training, LLM Frameworks | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [Chain-of-ThoughtsPapers](/tools/timothyxxx-chain-of-thoughtspapers.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 0d | 1010d | | Archived on GitHub | No | Yes | | Open issues (now) | 1.1k | 0 | | Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/timothyxxx-chain-of-thoughtspapers/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. ## Decision facts: Chain-of-ThoughtsPapers - **Adopt for:** Chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. - **Persona:** end user agent ## Choose when ### Choose LlamaFactory if… - 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. - More GitHub stars (73k vs 2.1k) - visibility, not fit. ### Choose Chain-of-ThoughtsPapers if… - Tags unique to Chain-of-ThoughtsPapers: gpt-3, chain-of-thought, prompt-learning, codex. - When you need insights into foundational and cutting-edge research on how language models can be prompted or structured to reason logically. - Leaner open-issue backlog (0). ## 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 Chain-of-ThoughtsPapers - If your focus is on unrelated areas such as image processing or speech recognition, where chain-of-thought reasoning in LLMs does not directly play a role. - For projects requiring immediate practical coding implementations — this repository primarily focuses on research and theoretical underpinnings rather than ready-to-use software libraries or codebases - In scenarios necessitating alternative approaches to language model training which do not emphasize step-by-step reasoning, such as models trained purely for pattern recognition without emphasis on a - what_is_missing ## Common questions ### What is the difference between LlamaFactory and Chain-of-ThoughtsPapers? LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. Chain-of-ThoughtsPapers: A curated list of papers exploring chain-of-thought reasoning in large language models.. See the comparison table for live GitHub stats and shared categories. ### When should I choose LlamaFactory over Chain-of-ThoughtsPapers? Choose LlamaFactory over Chain-of-ThoughtsPapers when 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; More GitHub stars (73k vs 2.1k) - visibility, not fit. ### When should I choose Chain-of-ThoughtsPapers over LlamaFactory? Choose Chain-of-ThoughtsPapers over LlamaFactory when Tags unique to Chain-of-ThoughtsPapers: gpt-3, chain-of-thought, prompt-learning, codex; When you need insights into foundational and cutting-edge research on how language models can be prompted or structured to reason logically; Leaner open-issue backlog (0). ### 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 Chain-of-ThoughtsPapers? If your focus is on unrelated areas such as image processing or speech recognition, where chain-of-thought reasoning in LLMs does not directly play a role. For projects requiring immediate practical coding implementations — this repository primarily focuses on research and theoretical underpinnings rather than ready-to-use software libraries or codebases In scenarios necessitating alternative approaches to language model training which do not emphasize step-by-step reasoning, such as models trained purely for pattern recognition without emphasis on a what_is_missing ### Is LlamaFactory or Chain-of-ThoughtsPapers more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 2,106). Stars measure visibility, not whether either tool fits your constraints. ### Are LlamaFactory and Chain-of-ThoughtsPapers open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to LlamaFactory or Chain-of-ThoughtsPapers? GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [Chain-of-ThoughtsPapers alternatives](/tools/timothyxxx-chain-of-thoughtspapers/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [Chain-of-ThoughtsPapers markdown twin](/tools/timothyxxx-chain-of-thoughtspapers/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-timothyxxx-chain-of-thoughtspapers.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LlamaFactory or Chain-of-ThoughtsPapers? LlamaFactory: Very active. Chain-of-ThoughtsPapers: 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 LlamaFactory and Chain-of-ThoughtsPapers? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [Chain-of-ThoughtsPapers trust report](/tools/timothyxxx-chain-of-thoughtspapers/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/_