ms-swift overview and key facts (October 2026)

ms-swift is an open-source framework from the ModelScope community that covers the full lifecycle of large models, from fine-tuning to evaluation and deployment. It supports a wide range of models such as Qwen, DeepSeek, Llama and GLM and runs on many kinds of hardware.

ms-swift combines training methods such as SFT, DPO and GRPO with parameter-efficient and full-parameter training, plus inference acceleration, quantization, evaluation and deployment. It runs on NVIDIA and AMD GPUs, Ascend NPUs, Apple MPS and CPUs. ModelScope, a community linked to Alibaba, maintains the project. The repository had about 15,700 stars and a last push on September 28, 2026.

• Fine-tunes many model familiesOne framework handles more than 600 language models and many multimodal models. Teams can switch base models without learning a new toolchain.
• Trains without codeThe Gradio web UI starts training and deployment from a browser. Teams with little machine learning engineering experience can run first experiments.
• Evaluates and deploys in one placeAfter training, the same framework evaluates, quantizes and serves the model. The path from experiment to a running service gets shorter.

• Supports Ascend NPUs and Apple MPS in addition to NVIDIA and AMD GPUs.
• Covers training, evaluation, quantization and deployment in one framework.

ms-swift is maintained by the Chinese ModelScope community and can be used worldwide without country ties.

Guides are available in English and Chinese, and the examples focus on models such as Qwen, DeepSeek and Llama, so check whether they cover your base model. Review the license of each base model separately. When you run the framework on your own hardware, data stays with you, but you handle updates and security.

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