---
title: "LlamaFactory vs tiger"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-tigerlab-ai-tiger"
tools: ["hiyouga-llamafactory", "tigerlab-ai-tiger"]
---

# LlamaFactory vs tiger

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick LlamaFactory when llamaFactory is primarily Python; tiger is Jupyter Notebook; pick tiger when tiger 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. [tiger](https://www.tigerlab.ai) has 403 stars, 27 forks, and 7 open issues, last pushed Dec 2, 2023. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [tiger's repository](https://github.com/tigerlab-ai/tiger).

| | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [tiger](/tools/tigerlab-ai-tiger.md) |
| --- | --- | --- |
| Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning) |
| Stars | 73,157 | 403 |
| Forks | 8,937 | 27 |
| Open issues | 1,067 | 7 |
| 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 | Apache-2.0 |
| 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) | [tiger](/tools/tigerlab-ai-tiger.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Dormant (18%) |
| Days since push | 0d | 952d |
| Open issues (now) | 1.1k | 7 |
| Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/tigerlab-ai-tiger/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; tiger is Jupyter Notebook.
- Tags unique to LlamaFactory: gemma, deepseek, ai, instruction-tuning.
- When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.

### Choose tiger if…

- tiger is primarily Jupyter Notebook; LlamaFactory is Python.
- Tags unique to tiger: ai-safety, llm, llm-training, data-augmentation.
- Also covers Vector Databases.

## 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 tiger

- Last GitHub push was 952 days ago (dormant maintenance, Dec 2, 2023). Validate activity before betting a new project on tiger.
- 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 tiger?

LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. tiger: Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning). See the comparison table for live GitHub stats and shared categories.

### When should I choose LlamaFactory over tiger?

Choose LlamaFactory over tiger when LlamaFactory is primarily Python; tiger is Jupyter Notebook; Tags unique to LlamaFactory: gemma, deepseek, ai, 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 tiger over LlamaFactory?

Choose tiger over LlamaFactory when tiger is primarily Jupyter Notebook; LlamaFactory is Python; Tags unique to tiger: ai-safety, llm, llm-training, data-augmentation; Also covers Vector Databases.

### 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 tiger?

Last GitHub push was 952 days ago (dormant maintenance, Dec 2, 2023). Validate activity before betting a new project on tiger. 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 tiger more popular on GitHub?

LlamaFactory has more GitHub stars (73,157 vs 403). Stars measure visibility, not whether either tool fits your constraints.

### Are LlamaFactory and tiger open source?

Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, tiger: Apache-2.0).

### Where can I find alternatives to LlamaFactory or tiger?

GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [tiger alternatives](/tools/tigerlab-ai-tiger/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [tiger markdown twin](/tools/tigerlab-ai-tiger/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-tigerlab-ai-tiger.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, LlamaFactory or tiger?

LlamaFactory: Very active. tiger: 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 tiger?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [tiger trust report](/tools/tigerlab-ai-tiger/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/_
