Elamur Research⌕
☰
home / papers / 2025 / Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Paper · 2025 · Tencent Hunyuan Team, Ao Liu, Botong Zhou et al.

Summary

Hunyuan-TurboS tackles the tension between strong LLM quality and inference cost, especially for long inputs and reasoning-heavy requests. The Tencent team built a hybrid Mixture-of-Experts model. It interleaves Mamba2 state-space layers, which scale linearly with sequence length, with a few Grouped-Query Attention layers and MoE feed-forward layers, arranged in alternating AMF and MF blocks.

Pre-training covers 16T tokens from a curated pipeline. The pipeline includes URL-level and semantic deduplication, block pruning, topic labelling, and dedicated math/code extraction. It is followed by annealing and staged context extension to 256K.

Post-training has four parts:

  • SFT on 3M instructions.
  • Adaptive Long-short CoT Fusion, which teaches the model when to reason at length and when to answer directly.
  • Multi-round Deliberation Learning, guided by LLM-judge ensembles and human experts.
  • Two GRPO reinforcement-learning stages, first for STEM and then for general instruction following.

The model reaches 1356 on LMSYS Chatbot Arena (top 7) and averages 77.9% over 23 automatic benchmarks. The work matters because it shows a Mamba-based hybrid can run in production at very large scale while lowering generation cost.

Key points

  • Architecture: 128 layers (57 Mamba2, 7 Attention, 64 FFN) with 560B total and 56B active parameters. The MoE uses 32 experts, routing each token to 1 shared and 2 specialized experts. The 128K-vocabulary tokenizer is reused from Hunyuan-Large.
  • Arena ranking: On LMSYS Chatbot Arena, TurboS (1356) edges out Gemini-2.0-Flash-001 (1352) and o4-mini-2025-04-16 (1345). It ranks first in the Chinese, French and Spanish categories.
  • Token efficiency: Adaptive CoT lets the model match a top reasoning model on Arena while using roughly half as many generated tokens.
  • Inference engine: The AngelHCF engine adds Mamba prefill/decode kernels and expert parallelism, giving a 1.8x speedup over Hunyuan-Turbo, a pure Transformer MoE.
  • State precision: Keeping Mamba states in fp32 curbs repetitive output and cuts token usage by 35–45% on math and competitive-programming tasks.
  • Training infrastructure: The Angel-RL framework supports TP, PP, EP and CP parallelism, and long-context extension relies on NTK-aware positional encoding.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Fields, topics and concepts

Cite

Cite as Tencent Hunyuan Team, Ao Liu, Botong Zhou, Can Xu, Chayse Zhou, ChenChen Zhang, Chengcheng Xu, Chenhao Wang, Decheng Wu, Dengpeng Wu, Dian Jiao, Dong Du, Dong Wang, Feng Zhang, Fengzong Lian, Guanghui Xu, Guanwei Zhang, Hai Wang, Haipeng Luo, Han Hu, Huilin Xu, Jiajia Wu, Jianchen Zhu, Jianfeng Yan, Jiaqi Zhu, Jihong Zhang, Jinbao Xue, Jun Xia, Junqiang Zheng, Kai Liu, Kai Zhang, Kai Zheng, Kejiao Li, Keyao Wang, Lan Jiang, Lixin Liu, Lulu Wu, Mengyuan Huang, Peijie Yu, Peiqi Wang, Qian Wang, Qianbiao Xiang, Qibin Liu, Qingfeng Sun, Richard Guo, Ruobing Xie, Saiyong Yang, Shaohua Chen, Shihui Hu, Shuai Li, Shuaipeng Li, Shuang Chen, Suncong Zheng, Tao Yang, Tian Zhang, Tinghao Yu, Weidong Han, Weijie Liu, Weijin Zhou, Weikang Wang, Wesleye Chen, Xiao Feng, Xiaoqin Ren, Xingwu Sun, Xiong Kuang, Xuemeng Huang, Xun Cao, Yanfeng Chen, Yang Du, Zhen Yang, Yangyu Tao, Yaping Deng, Yi Shen, Yigeng Hong, Yiqi Chen, Yiqing Huang, Yuchi Deng, Yue Mao, Yulong Wang, Yuyuan Zeng, Zenan Xu, Zhanhui Kang, Zhe Zhao, ZhenXiang Yan, Zheng Fang, Zhichao Hu, Zhongzhi Chen, Zhuoyu Li, Zongwei Li, Alex Yan, Ande Liang, Baitong Liu, Beiping Pan, Bin Xing, Binghong Wu, Bingxin Qu, Bolin Ni, Boyu Wu, Chen Li, Cheng Jiang, Cheng Zhang, Chengjun Liu, Chengxu Yang, Chengzhong Xu, Chiyu Wang, Chong Zha, Daisy Yi, Di Wang, Fanyang Lu, Fei Chen, Feifei Liu, Feng Zheng, Guanghua Yu, Guiyang Li, Guohua Wang, Haisheng Lin, Han Liu, Han Wang, Hao Fei, Hao Lu, Haoqing Jiang, Haoran Sun, Haotian Zhu, Huangjin Dai, Huankui Chen, Huawen Feng, Huihui Cai, Huxin Peng, Jackson Lv, Jiacheng Shi, Jiahao Bu, Jianbo Li, Jianglu Hu, Jiangtao Guan, Jianing Xu, Jianwei Cai, Jiarong Zhang, Jiawei Song, Jie Jiang, Jie Liu, Jieneng Yang, Jihong Zhang, Jin lv, Jing Zhao, Jinjian Li, Jinxing Liu, Jun Zhao, Juntao Guo, Kai Wang, Kan Wu, Lei Fu, Lei He, Lei Wang, Li Liu, Liang Dong, Liya Zhan, Long Cheng, Long Xu, Mao Zheng, Meng Liu, Mengkang Hu, Nanli Chen, Peirui Chen, Peng He, Pengju Pan, Pengzhi Wei, Qi Yang, Qi Yi, Roberts Wang, Rongpeng Chen, Rui Sun, Rui Yang, Ruibin Chen, Ruixu Zhou, Shaofeng Zhang, Sheng Zhang, Shihao Xu, Shuaishuai Chang, Shulin Liu, SiQi Wang, Songjia Feng, Songling Yuan, Tao Zhang, Tianjiao Lang, Tongkai Li, Wei Deng, Wei Li, Weichao Wang, Weigang Zhang, Weixuan Sun, Wen Ouyang, Wenxiang Jiao, Wenzhi Sun, Wenzhuo Jia, Xiang Zhang, Xiangyu He, Xianshun Ren, XiaoYing Zhu, Xiaolong Guo, Xiaoxue Li, Xiaoyu Ma, Xican Lu, Xinhua Feng, Xinting Huang, Xinyu Guan, Xirui Li, Xu Zhang, Xudong Gao, Xun Luo, Xuxiang Qi, Yangkun Chen, Yangyu Tao, Yanling Xiao, Yantao Mai, Yanze Chen, Yao Ding, Yeting Yang, YiFan Song, Yifan Yang, Yijiao Zhu, Yinhe Wu, Yixian Liu, Yong Yang, Yuanjun Cai, Yuanlin Tu, Yue Zhang, Yufei Huang, Yuhang Zhou, Yuhao Jiang, Yuhong Liu, Yuhui Hu, Yujin Lin, Yun Yang, Yunhao Wang, Yusong Zhang, Zekun Wu, Zelong Zhang, Zhan Yu, Zhaoliang Yang, Zhe Zhao, Zheng Li, Zhenyu Huang, Zhiguang Liu, Zhijiang Xu, Zhiqing Kui, Zhiyin Zeng, Zhiyuan Xiong, Zhuo Han, Zifan Wu, Zigang Geng, Zilong Zhao, Ziyan Tang, Ziyuan Zhu, Zonglei Zhu and Zhijiang Xu. 2025. Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought. arXiv:2505.15431.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.48550/arxiv.2505.15431 · arXiv 2505.15431

@misc{team2025hunyuan,
  title = {{Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought}},
  author = {Tencent Hunyuan Team, Ao Liu, Botong Zhou, Can Xu, Chayse Zhou, ChenChen Zhang, Chengcheng Xu, Chenhao Wang, Decheng Wu, Dengpeng Wu, Dian Jiao, Dong Du, Dong Wang, Feng Zhang, Fengzong Lian, Guanghui Xu, Guanwei Zhang, Hai Wang, Haipeng Luo, Han Hu, Huilin Xu, Jiajia Wu, Jianchen Zhu, Jianfeng Yan, Jiaqi Zhu, Jihong Zhang, Jinbao Xue, Jun Xia, Junqiang Zheng, Kai Liu, Kai Zhang, Kai Zheng, Kejiao Li, Keyao Wang, Lan Jiang, Lixin Liu, Lulu Wu, Mengyuan Huang, Peijie Yu, Peiqi Wang, Qian Wang, Qianbiao Xiang, Qibin Liu, Qingfeng Sun, Richard Guo, Ruobing Xie, Saiyong Yang, Shaohua Chen, Shihui Hu, Shuai Li, Shuaipeng Li, Shuang Chen, Suncong Zheng, Tao Yang, Tian Zhang, Tinghao Yu, Weidong Han, Weijie Liu, Weijin Zhou, Weikang Wang, Wesleye Chen, Xiao Feng, Xiaoqin Ren, Xingwu Sun, Xiong Kuang, Xuemeng Huang, Xun Cao, Yanfeng Chen, Yang Du, Zhen Yang, Yangyu Tao, Yaping Deng, Yi Shen, Yigeng Hong, Yiqi Chen, Yiqing Huang, Yuchi Deng, Yue Mao, Yulong Wang, Yuyuan Zeng, Zenan Xu, Zhanhui Kang, Zhe Zhao, ZhenXiang Yan, Zheng Fang, Zhichao Hu, Zhongzhi Chen, Zhuoyu Li, Zongwei Li, Alex Yan, Ande Liang, Baitong Liu, Beiping Pan, Bin Xing, Binghong Wu, Bingxin Qu, Bolin Ni, Boyu Wu, Chen Li, Cheng Jiang, Cheng Zhang, Chengjun Liu, Chengxu Yang, Chengzhong Xu, Chiyu Wang, Chong Zha, Daisy Yi, Di Wang, Fanyang Lu, Fei Chen, Feifei Liu, Feng Zheng, Guanghua Yu, Guiyang Li, Guohua Wang, Haisheng Lin, Han Liu, Han Wang, Hao Fei, Hao Lu, Haoqing Jiang, Haoran Sun, Haotian Zhu, Huangjin Dai, Huankui Chen, Huawen Feng, Huihui Cai, Huxin Peng, Jackson Lv, Jiacheng Shi, Jiahao Bu, Jianbo Li, Jianglu Hu, Jiangtao Guan, Jianing Xu, Jianwei Cai, Jiarong Zhang, Jiawei Song, Jie Jiang, Jie Liu, Jieneng Yang, Jihong Zhang, Jin lv, Jing Zhao, Jinjian Li, Jinxing Liu, Jun Zhao, Juntao Guo, Kai Wang, Kan Wu, Lei Fu, Lei He, Lei Wang, Li Liu, Liang Dong, Liya Zhan, Long Cheng, Long Xu, Mao Zheng, Meng Liu, Mengkang Hu, Nanli Chen, Peirui Chen, Peng He, Pengju Pan, Pengzhi Wei, Qi Yang, Qi Yi, Roberts Wang, Rongpeng Chen, Rui Sun, Rui Yang, Ruibin Chen, Ruixu Zhou, Shaofeng Zhang, Sheng Zhang, Shihao Xu, Shuaishuai Chang, Shulin Liu, SiQi Wang, Songjia Feng, Songling Yuan, Tao Zhang, Tianjiao Lang, Tongkai Li, Wei Deng, Wei Li, Weichao Wang, Weigang Zhang, Weixuan Sun, Wen Ouyang, Wenxiang Jiao, Wenzhi Sun, Wenzhuo Jia, Xiang Zhang, Xiangyu He, Xianshun Ren, XiaoYing Zhu, Xiaolong Guo, Xiaoxue Li, Xiaoyu Ma, Xican Lu, Xinhua Feng, Xinting Huang, Xinyu Guan, Xirui Li, Xu Zhang, Xudong Gao, Xun Luo, Xuxiang Qi, Yangkun Chen, Yangyu Tao, Yanling Xiao, Yantao Mai, Yanze Chen, Yao Ding, Yeting Yang, YiFan Song, Yifan Yang, Yijiao Zhu, Yinhe Wu, Yixian Liu, Yong Yang, Yuanjun Cai, Yuanlin Tu, Yue Zhang, Yufei Huang, Yuhang Zhou, Yuhao Jiang, Yuhong Liu, Yuhui Hu, Yujin Lin, Yun Yang, Yunhao Wang, Yusong Zhang, Zekun Wu, Zelong Zhang, Zhan Yu, Zhaoliang Yang, Zhe Zhao, Zheng Li, Zhenyu Huang, Zhiguang Liu, Zhijiang Xu, Zhiqing Kui, Zhiyin Zeng, Zhiyuan Xiong, Zhuo Han, Zifan Wu, Zigang Geng, Zilong Zhao, Ziyan Tang, Ziyuan Zhu, Zonglei Zhu and Zhijiang Xu},
  year = {2025},
  doi = {10.48550/arxiv.2505.15431},
  eprint = {2505.15431},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2505.15431}
}

References

59 references, 33 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, and Sumit Sanghai. Gqa: Training generalized multi-query transformer models from multi-head checkpoints, 2023. URL https://arxiv.org/abs/2305.13245. ↗
  2. Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, et al. Program synthesis with large language models. arXiv preprint arXiv:2108.07732, 2021.
  3. Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al. PIQA: Reasoning about physical commonsense in natural language. In Proceedings of AAAI, 2020.
  4. Federico Cassano, John Gouwar, Daniel Nguyen, Sydney Nguyen, Luna Phipps-Costin, Donald Pinckney, Ming-Ho Yee, Yangtian Zi, Carolyn Jane Anderson, Molly Q Feldman, et al. Multipl-e: A scalable and extensible approach to benchmarking neural code generation. arXiv preprint arXiv:2208.08227, 2022. find
  5. Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374, 2021.
  6. Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael Jordan, Joseph E Gonzalez, et al. Chatbot arena: An open platform for evaluating llms by human preference. In Forty-first International Conference on Machine Learning, 2…
  7. Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge. arXiv preprint arXiv:1803.05457, 2018.
  8. Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al. Training verifiers to solve math word problems. arXiv preprint arXiv:2110.14168, 2021.
  9. Tri Dao and Albert Gu. Transformers are ssms: Generalized models and efficient algorithms through structured state space duality. arXiv preprint arXiv:2405.21060, 2024. find
  10. Google DeepMind. Gemini 2.5, 2025. URL https://blog.google/technology/google-deepmind/gemini -model-thinking-updates-march-2025/. ↗
  11. DeepSeek-AI, Aixin Liu, Bei Feng, Bing Xue, Bingxuan Wang, Bochao Wu, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fucong Dai, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Han Bao, H… find
  12. Tim Dettmers, Mike Lewis, Younes Belkada, and Luke Zettlemoyer. Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale. Advances in neural information processing systems, 35:30318–30332, 2022. find
  13. Xinrun Du, Yifan Yao, Kaijing Ma, Bingli Wang, Tianyu Zheng, King Zhu, Minghao Liu, Yiming Liang, Xiaolong Jin, Zhenlin Wei, et al. Supergpqa: Scaling llm evaluation across 285 graduate disciplines. arXiv preprint arXiv:2502.14739, 2025. find
  14. Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner. Drop: A reading comprehension benchmark requiring discrete reasoning over paragraphs. arXiv preprint arXiv:1903.00161, 2019.
  15. Aryo Pradipta Gema, Joshua Ong Jun Leang, Giwon Hong, Alessio Devoto, Alberto Carlo Maria Mancino, Rohit Saxena, Xuanli He, Yu Zhao, Xiaotang Du, Mohammad Reza Ghasemi Madani, et al. Are we done with mmlu? arXiv preprint arXiv:2406.04127, 2024. find
  16. Albert Gu and Tri Dao. Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752, 2023. find
  17. Alex Gu, Baptiste Rozière, Hugh Leather, Armando Solar-Lezama, Gabriel Synnaeve, and Sida I Wang. Cruxeval: A benchmark for code reasoning, understanding and execution. arXiv preprint arXiv:2401.03065, 2024.
  18. Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al. DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning. arXiv preprint arXiv:2501.12948, 2025.
  19. Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. Measuring mathematical problem solving with the math dataset. arXiv preprint arXiv:2103.03874, 2021.
  20. Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang, Jinghan Zhang, Tangjun Su, Junteng Liu, Chuancheng Lv, Yikai Zhang, Yao Fu, et al. C-Eval: A multi-level multi-discipline chinese evaluation suite for foundation models. In Proceedings of NeurIPS, 2024.
  21. Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, and Ion Stoica. Livecodebench: Holistic and contamination free evaluation of large language models for code. arXiv preprint arXiv:2403.07974, 2024.
  22. Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer. TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension. arXiv preprint arXiv:1705.03551, 2017.
  23. Pei Ke, Bosi Wen, Zhuoer Feng, Xiao Liu, Xuanyu Lei, Jiale Cheng, Shengyuan Wang, Aohan Zeng, Yuxiao Dong, Hongning Wang, Jie Tang, and Minlie Huang. Critiquellm: Towards an informative critique generation model for evaluation of large language model generation, 2024. URL https://arxiv.org/abs/2311… ↗
  24. Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al. Natural questions: a benchmark for question answering research. TACL, 2019.
  25. Haonan Li, Yixuan Zhang, Fajri Koto, Yifei Yang, Hai Zhao, Yeyun Gong, Nan Duan, and Timothy Baldwin. CMMLU: Measuring massive multitask language understanding in chinese. arXiv preprint arXiv:2306.09212, 2023a.
  26. Wenhao Li, Fanchao Qi, Maosong Sun, Xiaoyuan Yi, and Jiarui Zhang. Ccpm: A chinese classical poetry matching dataset. arXiv preprint arXiv:2106.01979, 2021. — [arXiv:2106.01979](https://arxiv.org/abs/2106.01979) find
  27. Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason Weston, and Mike Lewis. Self-alignment with instruction backtranslation. arXiv preprint arXiv:2308.06259, 2023b.
  28. Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark, and Yejin Choi. Zebralogic: On the scaling limits of llms for logical reasoning, 2025. URL https://arxiv.org/abs/2502.01100. ↗
  29. Aixin Liu, Bei Feng, Bing Xue, Bingxuan Wang, Bochao Wu, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, et al. Deepseek-v3 technical report. arXiv preprint arXiv:2412.19437, 2024. find
  30. Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Jianguang Lou, Chongyang Tao, Xiubo Geng, Qingwei Lin, Shifeng Chen, and Dongmei Zhang. Wizardmath: Empowering mathematical reasoning for large language models via reinforced evol-instruct. arXiv preprint arXiv:2308.09583, 2023a.
  31. Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Qingwei Lin, Jian-Guang Lou, Shifeng Chen, Yansong Tang, and Weizhu Chen. Wizardarena: Post-training large language models via simulated offline chatbot arena. Advances in Neural Information Processing Systems, 37:111544–111570, 2024. find
  32. Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, and Daxin Jiang. Wizardcoder: Empowering code large language models with evol-instruct. arXiv preprint arXiv:2306.08568, 2023b. find
  33. Dakota Mahan, Duy Van Phung, Rafael Rafailov, Chase Blagden, Nathan Lile, Louis Castricato, Jan-Philipp Fränken, Chelsea Finn, and Alon Albalak. Generative reward models. arXiv preprint arXiv:2410.12832, 2024. find
  34. Meta. The llama 4 herd: The beginning of a new era of natively multimodal ai innovation. 2025. URL https://ai.meta.com/blog/llama-4-multimodal-intelligence/. ↗
  35. Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, and Bin Cui. Angel-ptm: A scalable and economical large-scale pre-training system in tencent. arXiv preprint arXiv:2303.02868, 2023. find
  36. OpenAI. Hello GPT-4o, 2024a. URL https://openai.com/index/hello-gpt-4o/. ↗
  37. OpenAI. Learning to reason with LLMs, 2024b. URL https://openai.com/index/learning-to-reaso n-with-llms/. ↗
  38. OpenAI. Introducing openai o3 and o4-mini, 2025. URL https://openai.com/index/introducing-o3-a nd-o4-mini/. ↗
  39. Bowen Peng and Jeffrey Quesnelle. Ntk-aware scaled rope allows llama models to have extended (8k+) context size without any fine-tuning and minimal perplexity degradation, 2023. find
  40. Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. WinoGrande: An adversarial winograd schema challenge at scale. Communications of the ACM, 2021. find
  41. Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, YK Li, Y Wu, et al. Deepseekmath: Pushing the limits of mathematical reasoning in open language models. arXiv preprint arXiv:2402.03300, 2024.
  42. Freda Shi, Mirac Suzgun, Markus Freitag, Xuezhi Wang, Suraj Srivats, Soroush Vosoughi, Hyung Won Chung, Yi Tay, Sebastian Ruder, Denny Zhou, et al. Language models are multilingual chain-of-thought reasoners. arXiv preprint arXiv:2210.03057, 2022.
  43. Xingwu Sun, Yanfeng Chen, Yiqing Huang, Ruobing Xie, Jiaqi Zhu, Kai Zhang, Shuaipeng Li, Zhen Yang, Jonny Han, Xiaobo Shu, et al. Hunyuan-large: An open-source moe model with 52 billion activated parameters by tencent. arXiv preprint arXiv:2411.02265, 2024.
  44. Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V Le, Ed H Chi, Denny Zhou, et al. Challenging big-bench tasks and whether chain-of-thought can solve them. arXiv preprint arXiv:2210.09261, 2022.
  45. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. Attention is all you need. In Proceedings of NIPS, 2017.
  46. Binjie Wang, Steffi Chern, Ethan Chern, and Pengfei Liu. Halu-j: Critique-based hallucination judge, 2024a. URL https://arxiv.org/abs/2407.12943. ↗
  47. Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. Self-instruct: Aligning language models with self-generated instructions. arXiv preprint arXiv:2212.10560, 2022. find
  48. Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, et al. MMLU-Pro: A more robust and challenging multi-task language understanding benchmark. In Proceedings of NeurIPS, 2024b.
  49. Tianwen Wei, Jian Luan, Wei Liu, Shuang Dong, and Bin Wang. CMATH: Can your language model pass chinese elementary school math test? arXiv preprint arXiv:2306.16636, 2023a.
  50. Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, and Lingming Zhang. Magicoder: Empowering code generation with oss-instruct. arXiv preprint arXiv:2312.02120, 2023b. find
  51. Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, and Lingming Zhang. Magicoder: Empowering code generation with OSS-instruct. In Proceedings of the 41st International Conference on Machine Learning, volume 235 of Proceedings of Machine Learning Research, pp. 52632–52657. PMLR, 21–27 Jul 2024. URL htt… find
  52. Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Qingwei Lin, and Daxin Jiang. Wizardlm: Empowering large pre-trained language models to follow complex instructions. In The Twelfth International Conference on Learning Representations, 2024.
  53. Wenyuan Xu, Xiaochen Zuo, Chao Xin, Yu Yue, Lin Yan, and Yonghui Wu. A unified pairwise framework for rlhf: Bridging generative reward modeling and policy optimization, 2025. URL https://arxiv.org/abs/2504.04950. — [arXiv:2504.04950](https://arxiv.org/abs/2504.04950) ↗
  54. An Yang, Anfeng Li, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Gao, Chengen Huang, Chenxu Lv, Chujie Zheng, Dayiheng Liu, Fan Zhou, Fei Huang, Feng Hu, Hao Ge, Haoran Wei, Huan Lin, Jialong Tang, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Yang, Jiaxi Yang, Jing Zhou, Jin… — Qwen3 Technical Report
  55. An Yang, Anfeng Li, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Gao, Chengen Huang, Chenxu Lv, et al. Qwen3 technical report. arXiv preprint arXiv:2505.09388, 2025b.
  56. Qiying Yu, Zheng Zhang, Ruofei Zhu, Yufeng Yuan, Xiaochen Zuo, Yu Yue, Tiantian Fan, Gaohong Liu, Lingjun Liu, Xin Liu, et al. Dapo: An open-source llm reinforcement learning system at scale, 2025. URL https://arxiv.org/abs/2503.14476. ↗
  57. Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. HellaSwag: Can a machine really finish your sentence? In Proceedings of ACL, 2019. find
  58. Weihao Zeng, Can Xu, Yingxiu Zhao, Jian-Guang Lou, and Weizhu Chen. Automatic instruction evolving for large language models. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 6998–7018, 2024.
  59. Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, and Rishabh Agarwal. Generative verifiers: Reward modeling as next-token prediction. arXiv preprint arXiv:2408.15240, 2024.

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuan-turbos-advancing-large/