--- title: "LlamaFactory vs RegaVAE" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-trustedllm-regavae" tools: ["hiyouga-llamafactory", "trustedllm-regavae"] --- # LlamaFactory vs RegaVAE *GraphCanon updated Jul 12, 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 RegaVAE if regaVAE brings a unique approach by integrating retrieval mechanisms with Gaussian Mixture VAEs to enhance language modeling. [LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [RegaVAE](https://github.com/TrustedLLM/RegaVAE) has 15 stars, 1 forks, and 0 open issues, last pushed Dec 5, 2023. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [RegaVAE's repository](https://github.com/TrustedLLM/RegaVAE). | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [RegaVAE](/tools/trustedllm-regavae.md) | | --- | --- | --- | | Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language Modeling | | Stars | 73,157 | 15 | | Forks | 8,937 | 1 | | Open issues | 1,067 | 0 | | 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. | RegaVAE brings a unique approach by integrating retrieval mechanisms with Gaussian Mixture VAEs to enhance language modeling. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | - | | Categories | LLM Frameworks, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [RegaVAE](/tools/trustedllm-regavae.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 949d | | Open issues (now) | 1.1k | 0 | | Owner type | User | Organization | | Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/trustedllm-regavae/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: RegaVAE - **Adopt for:** RegaVAE brings a unique approach by integrating retrieval mechanisms with Gaussian Mixture VAEs to enhance language modeling. ## Choose when ### Choose LlamaFactory if… - Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai. - Also covers LLM Frameworks. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### Choose RegaVAE if… - Tags unique to RegaVAE: language modeling, variational auto-encoder, retrieval-augmentation. - When seeking to leverage both historical and future information in the latent space for improved language generation. - 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 RegaVAE - If traditional Variational Auto-Encoders (VAEs) without retrieval components suffice for your needs, as RegaVAE introduces complexity that may not be necessary in simpler scenarios. - When dataset requirements exceed available resources or when datasets with specific formatting are hard to obtain and adapt. ## Common questions ### What is the difference between LlamaFactory and RegaVAE? LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. RegaVAE: A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language Modeling. See the comparison table for live GitHub stats and shared categories. ### When should I choose LlamaFactory over RegaVAE? Choose LlamaFactory over RegaVAE when Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; 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 choose RegaVAE over LlamaFactory? Choose RegaVAE over LlamaFactory when Tags unique to RegaVAE: language modeling, variational auto-encoder, retrieval-augmentation; When seeking to leverage both historical and future information in the latent space for improved language generation; 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 RegaVAE? If traditional Variational Auto-Encoders (VAEs) without retrieval components suffice for your needs, as RegaVAE introduces complexity that may not be necessary in simpler scenarios. When dataset requirements exceed available resources or when datasets with specific formatting are hard to obtain and adapt. ### Is LlamaFactory or RegaVAE more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 15). Stars measure visibility, not whether either tool fits your constraints. ### Are LlamaFactory and RegaVAE open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to LlamaFactory or RegaVAE? GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [RegaVAE alternatives](/tools/trustedllm-regavae/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [RegaVAE markdown twin](/tools/trustedllm-regavae/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-trustedllm-regavae.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LlamaFactory or RegaVAE? LlamaFactory: Very active. RegaVAE: 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 RegaVAE? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [RegaVAE trust report](/tools/trustedllm-regavae/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/_