⚡ TL;DR — 30-Second Verdict
Choose LLaMA-Factory if you want a GUI for fine-tuning, broad model support, and easy RLHF/DPO training — it's the most beginner-friendly fine-tuning framework. Choose Axolotl if you're a ML engineer who prefers config-file workflows, needs advanced DeepSpeed/FSDP integration, or wants more granular control over training dynamics.
Quick Comparison
| Feature | LLaMA-Factory | Axolotl |
|---|---|---|
| Interface | Web UI (LlamaBoard) + CLI | YAML config + CLI |
| Model support | 100+ models (Llama, Mistral, Qwen, etc.) | All major models via HF transformers |
| Fine-tune methods | LoRA, QLoRA, full, DPO, PPO, ORPO | LoRA, QLoRA, full, DPO, RLHF |
| DeepSpeed/FSDP | DeepSpeed support | DeepSpeed + FSDP support |
| Multi-GPU | Yes (DeepSpeed) | Yes (DeepSpeed + FSDP) |
| Beginner friendly | High (GUI available) | Moderate (config files) |
| Export formats | GGUF, vLLM, OpenAI-compatible | HuggingFace format |
What Is LLaMA-Factory?
LLaMA-Factory is the most comprehensive open-source fine-tuning toolkit for LLMs. It supports every major PEFT method (LoRA, QLoRA, DoRA, full fine-tuning) on 100+ model architectures via a single unified interface. If you're fine-tuning Llama, Qwen, Mistral, or DeepSeek models, this is where to start — the WebUI makes supervised fine-tuning accessible to ML engineers without a research background.
— AI Nav Editorial Team on LLaMA-Factory
→ Read the full LLaMA-Factory review
What Is Axolotl?
Axolotl is a focused tool that does one thing well. A practical tool for adapting pre-trained models to domain-specific tasks. LoRA fine-tuning has become the standard approach for most teams—full fine-tuning is only worth the additional cost if LoRA quality is insufficient for your use case.
— AI Nav Editorial Team on Axolotl
→ Read the full Axolotl review