--- title: "LlamaFactory vs RasaGPT" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-paulpierre-rasagpt" tools: ["hiyouga-llamafactory", "paulpierre-rasagpt"] --- # LlamaFactory vs RasaGPT *GraphCanon updated Jul 11, 2026* ## Verdict Pick LlamaFactory when license: LlamaFactory is Apache-2.0, RasaGPT is MIT; pick RasaGPT when license: RasaGPT is MIT, LlamaFactory is Apache-2.0. [LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [RasaGPT](https://rasagpt.dev) has 2.5k stars, 251 forks, and 57 open issues, last pushed Nov 12, 2025. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [RasaGPT's repository](https://github.com/paulpierre/RasaGPT). | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [RasaGPT](/tools/paulpierre-rasagpt.md) | | --- | --- | --- | | Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | 💬 RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram | | Stars | 73,157 | 2,464 | | Forks | 8,937 | 251 | | Open issues | 1,067 | 57 | | 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 | Apache-2.0 | MIT | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [RasaGPT](/tools/paulpierre-rasagpt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 240d | | Open issues (now) | 1.1k | 57 | | Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/paulpierre-rasagpt/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… - License: LlamaFactory is Apache-2.0, RasaGPT is MIT. - Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, instruction-tuning. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### Choose RasaGPT if… - License: RasaGPT is MIT, LlamaFactory is Apache-2.0. - Tags unique to RasaGPT: gpt-3, fastapi, gpt-4, chatgpt. - Also covers Vector Databases. - RasaGPT ships Docker support for self-hosted deployment. ## 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 RasaGPT - Last GitHub push was 241 days ago (slowing maintenance, Nov 12, 2025). Validate activity before betting a new project on RasaGPT. - 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. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between LlamaFactory and RasaGPT? LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. RasaGPT: 💬 RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram. See the comparison table for live GitHub stats and shared categories. ### When should I choose LlamaFactory over RasaGPT? Choose LlamaFactory over RasaGPT when License: LlamaFactory is Apache-2.0, RasaGPT is MIT; Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, instruction-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### When should I choose RasaGPT over LlamaFactory? Choose RasaGPT over LlamaFactory when License: RasaGPT is MIT, LlamaFactory is Apache-2.0; Tags unique to RasaGPT: gpt-3, fastapi, gpt-4, chatgpt; Also covers Vector Databases; RasaGPT ships Docker support for self-hosted deployment. ### 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 RasaGPT? Last GitHub push was 241 days ago (slowing maintenance, Nov 12, 2025). Validate activity before betting a new project on RasaGPT. 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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is LlamaFactory or RasaGPT more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 2,464). Stars measure visibility, not whether either tool fits your constraints. ### Are LlamaFactory and RasaGPT open source? Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, RasaGPT: MIT). ### Where can I find alternatives to LlamaFactory or RasaGPT? GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [RasaGPT alternatives](/tools/paulpierre-rasagpt/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [RasaGPT markdown twin](/tools/paulpierre-rasagpt/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-paulpierre-rasagpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LlamaFactory or RasaGPT? LlamaFactory: Very active. RasaGPT: Slowing. 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 RasaGPT? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [RasaGPT trust report](/tools/paulpierre-rasagpt/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/_