--- title: "knowledge-gpt vs LlamaFactory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/geeks-of-data-knowledge-gpt-vs-hiyouga-llamafactory" tools: ["geeks-of-data-knowledge-gpt", "hiyouga-llamafactory"] --- # knowledge-gpt vs LlamaFactory *GraphCanon updated Jul 12, 2026* ## Verdict Pick knowledge-gpt when license: knowledge-gpt is MIT, LlamaFactory is Apache-2.0; pick LlamaFactory when license: LlamaFactory is Apache-2.0, knowledge-gpt is MIT. [knowledge-gpt](https://pypi.org/project/knowledgegpt/) reports 291 GitHub stars, 52 forks, and 8 open issues, last pushed Apr 25, 2023. [LlamaFactory](https://llamafactory.readthedocs.io) has 73k stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [knowledge-gpt's repository](https://github.com/geeks-of-data/knowledge-gpt) and [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory). | | [knowledge-gpt](/tools/geeks-of-data-knowledge-gpt.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Tagline | Extract knowledge from various sources and perform Q&A sessions using GPT models | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | | Stars | 291 | 73,157 | | Forks | 52 | 8,937 | | Open issues | 8 | 1,067 | | Language | Python | 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. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [knowledge-gpt](/tools/geeks-of-data-knowledge-gpt.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1173d | 0d | | Open issues (now) | 8 | 1.1k | | Owner type | Organization | User | | Full report | [trust report](/tools/geeks-of-data-knowledge-gpt/trust.md) | [trust report](/tools/hiyouga-llamafactory/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 knowledge-gpt if… - License: knowledge-gpt is MIT, LlamaFactory is Apache-2.0. - Tags unique to knowledge-gpt: context, embedding, embedding-vectors, gpt3-turbo. - Also covers Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving. - knowledge-gpt ships Docker support for self-hosted deployment. ### Choose LlamaFactory if… - License: LlamaFactory is Apache-2.0, knowledge-gpt is MIT. - Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning. - Also covers LLM Frameworks. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ## When NOT to use knowledge-gpt - Last GitHub push was 1174 days ago (dormant maintenance, Apr 25, 2023). Validate activity before betting a new project on knowledge-gpt. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## 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 ## Common questions ### What is the difference between knowledge-gpt and LlamaFactory? knowledge-gpt: Extract knowledge from various sources and perform Q&A sessions using GPT models. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose knowledge-gpt over LlamaFactory? Choose knowledge-gpt over LlamaFactory when License: knowledge-gpt is MIT, LlamaFactory is Apache-2.0; Tags unique to knowledge-gpt: context, embedding, embedding-vectors, gpt3-turbo; Also covers Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving; knowledge-gpt ships Docker support for self-hosted deployment. ### When should I choose LlamaFactory over knowledge-gpt? Choose LlamaFactory over knowledge-gpt when License: LlamaFactory is Apache-2.0, knowledge-gpt is MIT; Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; Also covers LLM Frameworks; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### When should I avoid knowledge-gpt? Last GitHub push was 1174 days ago (dormant maintenance, Apr 25, 2023). Validate activity before betting a new project on knowledge-gpt. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### 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 ### Is knowledge-gpt or LlamaFactory more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 291). Stars measure visibility, not whether either tool fits your constraints. ### Are knowledge-gpt and LlamaFactory open source? Yes - both are open-source projects on GitHub (knowledge-gpt: MIT, LlamaFactory: Apache-2.0). ### Where can I find alternatives to knowledge-gpt or LlamaFactory? GraphCanon lists graph-backed alternatives at [knowledge-gpt alternatives](/tools/geeks-of-data-knowledge-gpt/alternatives) and [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) ([knowledge-gpt markdown twin](/tools/geeks-of-data-knowledge-gpt/alternatives.md), [LlamaFactory markdown twin](/tools/hiyouga-llamafactory/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/geeks-of-data-knowledge-gpt-vs-hiyouga-llamafactory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, knowledge-gpt or LlamaFactory? knowledge-gpt: Dormant. LlamaFactory: Very active. 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 knowledge-gpt and LlamaFactory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [knowledge-gpt trust report](/tools/geeks-of-data-knowledge-gpt/trust); [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=geeks-of-data-knowledge-gpt`](/api/graphcanon/graph?tool=geeks-of-data-knowledge-gpt) - 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/_