Unsloth vs Axolotl
Compare Unsloth and Axolotl on deployment, pricing, model support, and more.
Unsloth
- Tagline
- 2–5× faster LLM fine-tuning with 70% less memory — free open-source training library
- Description
- Unsloth is an open-source Python library that makes fine-tuning large language models 2–5× faster and 70% more memory-efficient. It achieves this through custom CUDA kernels and optimized implementations of key operations (RoPE, cross-entropy, attention). Supports Llama, Mistral, Gemma, Phi, and most popular open-source models. Free for single GPU; paid for multi-GPU.
- Category
- LLM Frameworks
- Pricing
- Freemium
- Metric
- 76,012 GitHub stars (source)
- Link
- Visit
Axolotl
- Tagline
- Open-source LLM fine-tuning framework — LoRA, QLoRA, and full fine-tuning for Llama, Mistral, and more
- Description
- Axolotl is an open-source Python framework for fine-tuning large language models. It supports LoRA, QLoRA, full fine-tuning, RLHF, and DPO training for Llama 3, Mistral, Mixtral, Phi, Falcon, and other models — configured via simple YAML files. Used extensively in the open-source AI community for creating specialized models and improving base models.
- Category
- LLM Frameworks
- Pricing
- Free
- Metric
- 12,460 GitHub stars (source)
- Link
- Visit
| Attribute | Unsloth | Axolotl |
|---|---|---|
| Tagline | 2–5× faster LLM fine-tuning with 70% less memory — free open-source training library | Open-source LLM fine-tuning framework — LoRA, QLoRA, and full fine-tuning for Llama, Mistral, and more |
| Category | LLM Frameworks | LLM Frameworks |
| Pricing | Freemium | Free |
| Description | Unsloth is an open-source Python library that makes fine-tuning large language models 2–5× faster and 70% more memory-efficient. It achieves this through custom CUDA kernels and optimized implementations of key operations (RoPE, cross-entropy, attention). Supports Llama, Mistral, Gemma, Phi, and most popular open-source models. Free for single GPU; paid for multi-GPU. | Axolotl is an open-source Python framework for fine-tuning large language models. It supports LoRA, QLoRA, full fine-tuning, RLHF, and DPO training for Llama 3, Mistral, Mixtral, Phi, Falcon, and other models — configured via simple YAML files. Used extensively in the open-source AI community for creating specialized models and improving base models. |
| Metric | 76,012 GitHub stars (source) | 12,460 GitHub stars (source) |
| Link | Visit | Visit |