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  Xwen is a series of open-sourced large language models (currently including **[Xwen-72B-Chat](https://huggingface.co/xwen-team/Xwen-72B-Chat)** and **[Xwen-7B-Chat](https://huggingface.co/xwen-team/Xwen-7B-Chat)**), post-trained from the pre-trained Qwen2.5 models (i.e., [Qwen2.5-72B](https://huggingface.co/Qwen/Qwen2.5-72B) and [Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B)) [1].
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- **πŸ† Top-1 chat performance!** To the best of our knowledge, at the time of Xwen models' release (February 1, 2025), **[Xwen-72B-Chat](https://huggingface.co/xwen-team/Xwen-72B-Chat) and [Xwen-7B-Chat](https://huggingface.co/xwen-team/Xwen-7B-Chat) exhibit the best chat performance among open-sourced models below 100B and 10B, respectively**, based on evaluation results from widely-used benchmarks such as Arena-Hard-Auto [2], MT-Bench [3], and AlignBench [4]. Please view details in the [Evaluation Results](https://huggingface.co/xwen-team/Xwen-72B-Chat#3-evaluation-results) part.
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  **πŸš€ Xwen technical report is on the way!** During the training of Xwen models, we have accumulated many technical insights and lessons. To promote the democratization of technology, we are in the process of documenting these insights and lessons in a technical report, which will be released as soon as possible.
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  Xwen is a series of open-sourced large language models (currently including **[Xwen-72B-Chat](https://huggingface.co/xwen-team/Xwen-72B-Chat)** and **[Xwen-7B-Chat](https://huggingface.co/xwen-team/Xwen-7B-Chat)**), post-trained from the pre-trained Qwen2.5 models (i.e., [Qwen2.5-72B](https://huggingface.co/Qwen/Qwen2.5-72B) and [Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B)) [1].
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+ **πŸ† Top-1 chat performance!** To the best of our knowledge, at the time of Xwen models' release (February 1, 2025), **[Xwen-72B-Chat](https://huggingface.co/xwen-team/Xwen-72B-Chat) and [Xwen-7B-Chat](https://huggingface.co/xwen-team/Xwen-7B-Chat) exhibit the best chat performance among open-sourced models below 100B and 10B, respectively**, based on evaluation results from widely-used benchmarks such as Arena-Hard-Auto [2], MT-Bench [3], and AlignBench [4]. Please view details in the [Evaluation Results](https://huggingface.co/xwen-team/Xwen-7B-Chat#3-evaluation-results) part.
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  **πŸš€ Xwen technical report is on the way!** During the training of Xwen models, we have accumulated many technical insights and lessons. To promote the democratization of technology, we are in the process of documenting these insights and lessons in a technical report, which will be released as soon as possible.
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