axolotl vs LlamaFactory
LLM fine-tuning frameworks compared
axolotl and LlamaFactory are Python frameworks for fine-tuning language models, with support for parameter-efficient methods and multimodal workflows. axolotl emphasizes YAML-configured training and distributed options, while LlamaFactory offers both a CLI and a Gradio web interface, plus inference and model export workflows.
axolotl: Fine-Tune Large Language Models
Axolotl is a Python framework for fine-tuning and post-training language models through configurable workflows. It supports methods from LoRA and QLoRA to preference tuning and reinforcement learning, with options for multimodal and distributed training.
LlamaFactory: Fine-Tune Large Language and Vision Models
LlamaFactory provides CLI and web interfaces for fine-tuning a broad range of language and vision models. It supports parameter-efficient methods and preference training, with workflows for training, inference, and model export.
| axolotl | LlamaFactory | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Stars | 12.5k | 75.3k |
| Forks | 1.5k | 9.2k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- axolotl uses YAML configuration across preprocessing, training, evaluation, quantization, and inference; LlamaFactory provides CLI commands and a Gradio-based web interface.
- axolotl lists DPO, IPO, KTO, ORPO, GRPO, and reward-model training; LlamaFactory lists preference and reinforcement-learning methods including DPO and PPO.
- axolotl names FSDP2, DeepSpeed, and multi-node workflows for distributed training; LlamaFactory highlights integrations such as vLLM, SGLang, experiment tracking, and selected acceleration tools.
- axolotl describes workflows for supported vision, audio, and video models; LlamaFactory also covers text, image, video, and audio-related tasks, depending on the model and workflow.
- LlamaFactory includes workflows for inference and exporting merged checkpoints; axolotl describes inference as part of its consistent workflow.
- Both projects use Python and have an Apache-2.0 license; the supplied figures list 12.5k stars and 1.5k forks for axolotl, and 75.3k stars and 9.2k forks for LlamaFactory.
Choose axolotl if you…
- need YAML configuration spanning dataset preparation, training, evaluation, quantization, and inference.
- want named distributed-training options such as FSDP2, DeepSpeed, or multi-node workflows.
- plan to explore preference-tuning methods including IPO, KTO, ORPO, or GRPO.
Choose LlamaFactory if you…
- want both a CLI and a Gradio web interface for common tasks.
- need workflows that include inference and exporting merged model checkpoints.
- want to work with a broad selection of language and vision models, including families such as Llama, Qwen, Gemma, and DeepSeek.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.