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

# LlamaFactory vs octoml-profile

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick LlamaFactory when tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; pick octoml-profile when also covers Speech & Audio.

[LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [octoml-profile](https://github.com/octoml/octoml-profile) has 114 stars, 10 forks, and 0 open issues, last pushed Apr 24, 2023. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [octoml-profile's repository](https://github.com/octoml/octoml-profile).

| | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [octoml-profile](/tools/octoml-octoml-profile.md) |
| --- | --- | --- |
| Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | Home for OctoML PyTorch Profiler |
| Stars | 73,157 | 114 |
| Forks | 8,937 | 10 |
| 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. | - |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | Apache-2.0 |
| Categories | LLM Frameworks, Model Training | Model Training, LLM Frameworks, Speech & Audio |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [octoml-profile](/tools/octoml-octoml-profile.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Dormant (18%) |
| Days since push | 0d | 1174d |
| Open issues (now) | 1.1k | 0 |
| Owner type | User | Organization |
| Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/octoml-octoml-profile/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…

- 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 114) - visibility, not fit.

### Choose octoml-profile if…

- Also covers Speech & Audio.
- 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 octoml-profile

- Last GitHub push was 1174 days ago (dormant maintenance, Apr 24, 2023). Validate activity before betting a new project on octoml-profile.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

## Common questions

### What is the difference between LlamaFactory and octoml-profile?

LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. octoml-profile: Home for OctoML PyTorch Profiler. See the comparison table for live GitHub stats and shared categories.

### When should I choose LlamaFactory over octoml-profile?

Choose LlamaFactory over octoml-profile 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 114) - visibility, not fit.

### When should I choose octoml-profile over LlamaFactory?

Choose octoml-profile over LlamaFactory when Also covers Speech & Audio; 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 octoml-profile?

Last GitHub push was 1174 days ago (dormant maintenance, Apr 24, 2023). Validate activity before betting a new project on octoml-profile. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

### Is LlamaFactory or octoml-profile more popular on GitHub?

LlamaFactory has more GitHub stars (73,157 vs 114). Stars measure visibility, not whether either tool fits your constraints.

### Are LlamaFactory and octoml-profile open source?

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

### Where can I find alternatives to LlamaFactory or octoml-profile?

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

### Which is better maintained, LlamaFactory or octoml-profile?

LlamaFactory: Very active. octoml-profile: 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 octoml-profile?

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