<|media_start|> 存在错误,已在聊天模板中替换为 <|media_begin|>。Kimi K2.5 是一款开源的原生多模态智能体模型,它在 Kimi-K2-Base 的基础上,通过对约 15 万亿混合视觉和文本 tokens 进行持续预训练构建而成。该模型将视觉与语言理解、高级智能体能力、即时模式与思考模式,以及对话式与智能体范式无缝融合。
| 架构 | 混合专家模型(Mixture-of-Experts, MoE) |
| 总参数 | 1T |
| 激活参数 | 32B |
| 层数(包含密集层) | 61 |
| 密集层层数 | 1 |
| 注意力隐藏维度 | 7168 |
| MoE 隐藏维度(每专家) | 2048 |
| 注意力头数 | 64 |
| 专家数量 | 384 |
| 每 Token 选择专家数 | 8 |
| 共享专家数量 | 1 |
| 词汇表大小 | 160K |
| 上下文长度 | 256K |
| 注意力机制 | MLA |
| 激活函数 | SwiGLU |
| 视觉编码器 | MoonViT |
| 视觉编码器参数 | 400M |
| 基准测试 | Kimi K2.5 (思考模式) | GPT-5.2 (超高配置) | Claude 4.5 Opus (扩展思考模式) | Gemini 3 Pro (高级思考水平) | DeepSeek V3.2 (思考模式) | Qwen3-VL- 235B-A22B- Thinking | |
|---|---|---|---|---|---|---|---|
| 推理与知识 | |||||||
| HLE-Full | 30.1 | 34.5 | 30.8 | 37.5 | 25.1† | - | |
| HLE-Full (使用工具) | 50.2 | 45.5 | 43.2 | 45.8 | 40.8† | - | |
| AIME 2025 | 96.1 | 100 | 92.8 | 95.0 | 93.1 | - | |
| HMMT 2025(2月) | 95.4 | 99.4 | 92.9* | 97.3* | 92.5 | - | |
| IMO-AnswerBench | 81.8 | 86.3 | 78.5* | 83.1* | 78.3 | - | |
| GPQA-Diamond | 87.6 | 92.4 | 87.0 | 91.9 | 82.4 | - | |
| MMLU-Pro | 87.1 | 86.7* | 89.3* | 90.1 | 85.0 | - | |
| 图像与视频 | |||||||
| MMMU-Pro | 78.5 | 79.5* | 74.0 | 81.0 | - | 69.3 | |
| CharXiv(RQ) | 77.5 | 82.1 | 67.2* | 81.4 | - | 66.1 | |
| MathVision | 84.2 | 83.0 | 77.1* | 86.1* | - | 74.6 | |
| MathVista(精简版) | 90.1 | 82.8* | 80.2* | 89.8* | - | 85.8 | |
| ZeroBench | 9 | 9* | 3* | 8* | - | 4* | |
| ZeroBench (使用工具) | 11 | 7* | 9* | 12* | - | 3* | |
| OCRBench | 92.3 | 80.7* | 86.5* | 90.3* | - | 87.5 | |
| OmniDocBench 1.5 | 88.8 | 85.7 | 87.7* | 88.5 | - | 82.0* | |
| InfoVQA(验证集) | 92.6 | 84* | 76.9* | 57.2* | - | 89.5 | |
| SimpleVQA | 71.2 | 55.8* | 69.7* | 69.7* | - | 56.8* | |
| WorldVQA | 46.3 | 28.0 | 36.8 | 47.4 | - | 23.5 | |
| VideoMMMU | 86.6 | 85.9 | 84.4* | 87.6 | - | 80.0 | |
| MMVU | 80.4 | 80.8* | 77.3 | 77.5 | - | 71.1 | |
| MotionBench | 70.4 | 64.8 | 60.3 | 70.3 | - | - | |
| VideoMME | 87.4 | 86.0* | - | 88.4* | - | 79.0 | |
| LongVideoBench | 79.8 | 76.5* | 67.2* | 77.7* | - | 65.6* | |
| LVBench | 75.9 | - | - | 73.5* | - | 63.6 | |
| 代码能力 | |||||||
| SWE-Bench Verified | 76.8 | 80.0 | 80.9 | 76.2 | 73.1 | - | |
| SWE-Bench Pro | 50.7 | 55.6 | 55.4* | - | - | - | |
| SWE-Bench Multilingual | 73.0 | 72.0 | 77.5 | 65.0 | 70.2 | - | |
| Terminal Bench 2.0 | 50.8 | 54.0 | 59.3 | 54.2 | 46.4 | - | |
| PaperBench | 63.5 | 63.7* | 72.9* | - | 47.1 | - | |
| CyberGym | 41.3 | - | 50.6 | 39.9* | 17.3* | - | |
| SciCode | 48.7 | 52.1 | 49.5 | 56.1 | 38.9 | - | |
| OJBench(cpp) | 57.4 | - | 54.6* | 68.5* | 54.7* | - | |
| LiveCodeBench(v6) | 85.0 | - | 82.2* | 87.4* | 83.3 | - | |
| 长文本上下文 | |||||||
| Longbench v2 | 61.0 | 54.5* | 64.4* | 68.2* | 59.8* | - | |
| AA-LCR | 70.0 | 72.3* | 71.3* | 65.3* | 64.3* | - | |
| 智能体搜索 | |||||||
| BrowseComp | 60.6 | 65.8 | 37.0 | 37.8 | 51.4 | - | |
| BrowseComp (带上下文管理) | 74.9 | 57.8 | 59.2 | 67.6 | - | ||
| BrowseComp (智能体集群) | 78.4 | - | - | - | - | - | |
| WideSearch (item-f1) | 72.7 | - | 76.2* | 57.0 | 32.5* | - | |
| WideSearch (item-f1 智能体集群) | 79.0 | - | - | - | - | - | |
| DeepSearchQA | 77.1 | 71.3* | 76.1* | 63.2* | 60.9* | - | |
| FinSearchCompT2&T3 | 67.8 | - | 66.2* | 49.9 | 59.1* | - | |
| Seal-0 | 57.4 | 45.0 | 47.7* | 45.5* | 49.5* | - | |
Kimi-K2.5 采用与 Kimi-K2-Thinking 相同的原生 int4 量化方法。
[!Note] 您可以通过 https://platform.moonshot.ai 访问 Kimi-K2.5 的 API,我们提供与 OpenAI/Anthropic 兼容的 API。为验证部署是否正确,我们还提供了 Kimi Vendor Verifier。 目前,建议在以下推理引擎上运行 Kimi-K2.5:
transformers 的最低版本要求为 4.57.1。
部署示例可参见 模型部署指南。
以下使用示例演示如何调用我们的官方 API。
对于使用 vLLM 或 SGLang 部署的第三方 API,请注意:
[!Note]
视频内容对话是一项实验性功能,目前仅在我们的官方 API 中支持。
思考模式(Thinking mode)推荐的
temperature为1.0,即时模式(Instant mode)推荐的temperature为0.6。推荐的
top_p为0.95。若要使用即时模式,需在
extra_body中传入{'chat_template_kwargs': {"thinking": False}}。
以下是一个简单的聊天补全脚本,展示如何在思考模式和即时模式下调用 K2.5 API。
import openai
import base64
import requests
def simple_chat(client: openai.OpenAI, model_name: str):
messages = [
{'role': 'system', 'content': 'You are Kimi, an AI assistant created by Moonshot AI.'},
{
'role': 'user',
'content': [
{'type': 'text', 'text': 'which one is bigger, 9.11 or 9.9? think carefully.'}
],
},
]
response = client.chat.completions.create(
model=model_name, messages=messages, stream=False, max_tokens=4096
)
print('====== Below is reasoning_content in Thinking Mode ======')
print(f'reasoning content: {response.choices[0].message.reasoning_content}')
print('====== Below is response in Thinking Mode ======')
print(f'response: {response.choices[0].message.content}')
# To use instant mode, pass {"thinking" = {"type":"disabled"}}
response = client.chat.completions.create(
model=model_name,
messages=messages,
stream=False,
max_tokens=4096,
extra_body={'thinking': {'type': 'disabled'}}, # this is for official API
# extra_body= {'chat_template_kwargs': {"thinking": False}} # this is for vLLM/SGLang
)
print('====== Below is response in Instant Mode ======')
print(f'response: {response.choices[0].message.content}')K2.5 支持图像和视频输入。
以下示例展示了如何使用图像输入调用 K2.5 API:
import openai
import base64
import requests
def chat_with_image(client: openai.OpenAI, model_name: str):
url = 'https://huggingface.co/moonshotai/Kimi-K2.5/resolve/main/figures/kimi-logo.png'
image_base64 = base64.b64encode(requests.get(url).content).decode()
messages = [
{
'role': 'user',
'content': [
{
'type': 'image_url',
'image_url': {'url': f'data:image/png;base64, {image_base64}'},
},
{'type': 'text', 'text': 'Describe this image in detail.'},
],
}
]
response = client.chat.completions.create(
model=model_name, messages=messages, stream=False, max_tokens=8192
)
print('====== Below is reasoning_content in Thinking Mode ======')
print(f'reasoning content: {response.choices[0].message.reasoning_content}')
print('====== Below is response in Thinking Mode ======')
print(f'response: {response.choices[0].message.content}')
# Also support instant mode if you pass {"thinking" = {"type":"disabled"}}
response = client.chat.completions.create(
model=model_name,
messages=messages,
stream=False,
max_tokens=4096,
extra_body={'thinking': {'type': 'disabled'}}, # this is for official API
# extra_body= {'chat_template_kwargs': {"thinking": False}} # this is for vLLM/SGLang
)
print('====== Below is response in Instant Mode ======')
print(f'response: {response.choices[0].message.content}')
return response.choices[0].message.content以下示例展示了如何使用视频输入调用 K2.5 API:
import openai
import base64
import requests
def chat_with_video(client: openai.OpenAI, model_name:str):
url = 'https://huggingface.co/moonshotai/Kimi-K2.5/resolve/main/figures/demo_video.mp4'
video_base64 = base64.b64encode(requests.get(url).content).decode()
messages = [
{
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {"url": f"data:video/mp4;base64,{video_base64}"},
},
{"type": "text","text": "Describe the video in detail."},
],
}
]
response = client.chat.completions.create(model=model_name, messages=messages)
print('====== Below is reasoning_content in Thinking Mode ======')
print(f'reasoning content: {response.choices[0].message.reasoning_content}')
print('====== Below is response in Thinking Mode ======')
print(f'response: {response.choices[0].message.content}')
# Also support instant mode if pass {"thinking" = {"type":"disabled"}}
response = client.chat.completions.create(
model=model_name,
messages=messages,
stream=False,
max_tokens=4096,
extra_body={'thinking': {'type': 'disabled'}}, # this is for official API
# extra_body= {'chat_template_kwargs': {"thinking": False}} # this is for vLLM/SGLang
)
print('====== Below is response in Instant Mode ======')
print(f'response: {response.choices[0].message.content}')
return response.choices[0].message.contentK2.5 沿用了与 K2 Thinking 相同的交错思维与多步工具调用设计。使用示例请参考 K2 Thinking 文档。
Kimi K2.5 与 Kimi Code CLI 作为其智能体框架配合使用时效果最佳,欢迎访问 https://www.kimi.com/code 体验。
代码仓库和模型权重均基于 Modified MIT License 发布。
如有任何问题,请通过 support@moonshot.cn 与我们联系。
如果您发现 K2.5 对您的研究有所帮助,敬请引用 K2.5 技术报告,格式如下:
@misc{kimiteam2026kimik25visualagentic,
title={Kimi K2.5: Visual Agentic Intelligence},
author={Kimi Team and Tongtong Bai and Yifan Bai and Yiping Bao and S. H. Cai and Yuan Cao and Y. Charles and H. S. Che and Cheng Chen and Guanduo Chen and Huarong Chen and Jia Chen and Jiahao Chen and Jianlong Chen and Jun Chen and Kefan Chen and Liang Chen and Ruijue Chen and Xinhao Chen and Yanru Chen and Yanxu Chen and Yicun Chen and Yimin Chen and Yingjiang Chen and Yuankun Chen and Yujie Chen and Yutian Chen and Zhirong Chen and Ziwei Chen and Dazhi Cheng and Minghan Chu and Jialei Cui and Jiaqi Deng and Muxi Diao and Hao Ding and Mengfan Dong and Mengnan Dong and Yuxin Dong and Yuhao Dong and Angang Du and Chenzhuang Du and Dikang Du and Lingxiao Du and Yulun Du and Yu Fan and Shengjun Fang and Qiulin Feng and Yichen Feng and Garimugai Fu and Kelin Fu and Hongcheng Gao and Tong Gao and Yuyao Ge and Shangyi Geng and Chengyang Gong and Xiaochen Gong and Zhuoma Gongque and Qizheng Gu and Xinran Gu and Yicheng Gu and Longyu Guan and Yuanying Guo and Xiaoru Hao and Weiran He and Wenyang He and Yunjia He and Chao Hong and Hao Hu and Jiaxi Hu and Yangyang Hu and Zhenxing Hu and Ke Huang and Ruiyuan Huang and Weixiao Huang and Zhiqi Huang and Tao Jiang and Zhejun Jiang and Xinyi Jin and Yu Jing and Guokun Lai and Aidi Li and C. Li and Cheng Li and Fang Li and Guanghe Li and Guanyu Li and Haitao Li and Haoyang Li and Jia Li and Jingwei Li and Junxiong Li and Lincan Li and Mo Li and Weihong Li and Wentao Li and Xinhang Li and Xinhao Li and Yang Li and Yanhao Li and Yiwei Li and Yuxiao Li and Zhaowei Li and Zheming Li and Weilong Liao and Jiawei Lin and Xiaohan Lin and Zhishan Lin and Zichao Lin and Cheng Liu and Chenyu Liu and Hongzhang Liu and Liang Liu and Shaowei Liu and Shudong Liu and Shuran Liu and Tianwei Liu and Tianyu Liu and Weizhou Liu and Xiangyan Liu and Yangyang Liu and Yanming Liu and Yibo Liu and Yuanxin Liu and Yue Liu and Zhengying Liu and Zhongnuo Liu and Enzhe Lu and Haoyu Lu and Zhiyuan Lu and Junyu Luo and Tongxu Luo and Yashuo Luo and Long Ma and Yingwei Ma and Shaoguang Mao and Yuan Mei and Xin Men and Fanqing Meng and Zhiyong Meng and Yibo Miao and Minqing Ni and Kun Ouyang and Siyuan Pan and Bo Pang and Yuchao Qian and Ruoyu Qin and Zeyu Qin and Jiezhong Qiu and Bowen Qu and Zeyu Shang and Youbo Shao and Tianxiao Shen and Zhennan Shen and Juanfeng Shi and Lidong Shi and Shengyuan Shi and Feifan Song and Pengwei Song and Tianhui Song and Xiaoxi Song and Hongjin Su and Jianlin Su and Zhaochen Su and Lin Sui and Jinsong Sun and Junyao Sun and Tongyu Sun and Flood Sung and Yunpeng Tai and Chuning Tang and Heyi Tang and Xiaojuan Tang and Zhengyang Tang and Jiawen Tao and Shiyuan Teng and Chaoran Tian and Pengfei Tian and Ao Wang and Bowen Wang and Chensi Wang and Chuang Wang and Congcong Wang and Dingkun Wang and Dinglu Wang and Dongliang Wang and Feng Wang and Hailong Wang and Haiming Wang and Hengzhi Wang and Huaqing Wang and Hui Wang and Jiahao Wang and Jinhong Wang and Jiuzheng Wang and Kaixin Wang and Linian Wang and Qibin Wang and Shengjie Wang and Shuyi Wang and Si Wang and Wei Wang and Xiaochen Wang and Xinyuan Wang and Yao Wang and Yejie Wang and Yipu Wang and Yiqin Wang and Yucheng Wang and Yuzhi Wang and Zhaoji Wang and Zhaowei Wang and Zhengtao Wang and Zhexu Wang and Zihan Wang and Zizhe Wang and Chu Wei and Ming Wei and Chuan Wen and Zichen Wen and Chengjie Wu and Haoning Wu and Junyan Wu and Rucong Wu and Wenhao Wu and Yuefeng Wu and Yuhao Wu and Yuxin Wu and Zijian Wu and Chenjun Xiao and Jin Xie and Xiaotong Xie and Yuchong Xie and Yifei Xin and Bowei Xing and Boyu Xu and Jianfan Xu and Jing Xu and Jinjing Xu and L. H. Xu and Lin Xu and Suting Xu and Weixin Xu and Xinbo Xu and Xinran Xu and Yangchuan Xu and Yichang Xu and Yuemeng Xu and Zelai Xu and Ziyao Xu and Junjie Yan and Yuzi Yan and Guangyao Yang and Hao Yang and Junwei Yang and Kai Yang and Ningyuan Yang and Ruihan Yang and Xiaofei Yang and Xinlong Yang and Ying Yang and Yi Yang and Yi Yang and Zhen Yang and Zhilin Yang and Zonghan Yang and Haotian Yao and Dan Ye and Wenjie Ye and Zhuorui Ye and Bohong Yin and Chengzhen Yu and Longhui Yu and Tao Yu and Tianxiang Yu and Enming Yuan and Mengjie Yuan and Xiaokun Yuan and Yang Yue and Weihao Zeng and Dunyuan Zha and Haobing Zhan and Dehao Zhang and Hao Zhang and Jin Zhang and Puqi Zhang and Qiao Zhang and Rui Zhang and Xiaobin Zhang and Y. Zhang and Yadong Zhang and Yangkun Zhang and Yichi Zhang and Yizhi Zhang and Yongting Zhang and Yu Zhang and Yushun Zhang and Yutao Zhang and Yutong Zhang and Zheng Zhang and Chenguang Zhao and Feifan Zhao and Jinxiang Zhao and Shuai Zhao and Xiangyu Zhao and Yikai Zhao and Zijia Zhao and Huabin Zheng and Ruihan Zheng and Shaojie Zheng and Tengyang Zheng and Junfeng Zhong and Longguang Zhong and Weiming Zhong and M. Zhou and Runjie Zhou and Xinyu Zhou and Zaida Zhou and Jinguo Zhu and Liya Zhu and Xinhao Zhu and Yuxuan Zhu and Zhen Zhu and Jingze Zhuang and Weiyu Zhuang and Ying Zou and Xinxing Zu},
year={2026},
eprint={2602.02276},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2602.02276},
}