ms-swift and LlamaFactory

Both are unified fine-tuning frameworks that support similar methods (LoRA, QLoRA, DPO) across large model families, making them direct competitors offering largely overlapping functionality rather than complementary tools.

ms-swift
91
Verified
LlamaFactory
70
Verified
Maintenance 25/25
Adoption 21/25
Maturity 25/25
Community 20/25
Maintenance 23/25
Adoption 10/25
Maturity 16/25
Community 21/25
Stars: 13,105
Forks: 1,255
Downloads: 97,941
Commits (30d): 103
Language: Python
License: Apache-2.0
Stars: 68,347
Forks: 8,346
Downloads:
Commits (30d): 24
Language: Python
License: Apache-2.0
No risk flags
No Package No Dependents

About ms-swift

modelscope/ms-swift

Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.5, DeepSeek-R1, GLM-5, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Llava, Phi4, ...) (AAAI 2025).

About LlamaFactory

hiyouga/LlamaFactory

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

Supports modular fine-tuning approaches including supervised fine-tuning, reward modeling, and reinforcement learning methods (PPO, DPO, KTO, ORPO), with optimizations like Flash Attention, quantized LoRA, and advanced optimizers (GaLore, BAdam, Muon). Provides both CLI and Gradio web interface for model training and inference, integrating with vLLM/SGLang for OpenAI-compatible API deployment.

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