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 ## 🚀 What's New <a><img width="35" height="20" src="https://user-images.githubusercontent.com/12782558/212848161-5e783dd6-11e8-4fe0-bbba-39ffb77730be.png"></a>
 
+- **\[2023.12.10\]** We have released [VLMEvalKit](https://github.com/open-compass/VLMEvalKit), a toolkit for evaluating vision-language models (VLMs), currently support 20+ VLMs and 7 multi-modal benchmarks (including MMBench series). 🔥🔥🔥.
 - **\[2023.12.10\]** We have supported Mistral AI's MoE LLM: **Mixtral-8x7B-32K**. Welcome to [MixtralKit](https://github.com/open-compass/MixtralKit) for more details about inference and evaluation. 🔥🔥🔥.
 - **\[2023.11.22\]** We have supported many API-based models, include **Baidu, ByteDance, Huawei, 360**. Welcome to [Models](https://opencompass.readthedocs.io/en/latest/user_guides/models.html) section for more details. 🔥🔥🔥.
 - **\[2023.11.20\]** Thanks [helloyongyang](https://github.com/helloyongyang) for supporting the evaluation with [LightLLM](https://github.com/ModelTC/lightllm) as backent. Welcome to [Evaluation With LightLLM](https://opencompass.readthedocs.io/en/latest/advanced_guides/evaluation_lightllm.html) for more details. 🔥🔥🔥.
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 ## 🚀 最新进展 <a><img width="35" height="20" src="https://user-images.githubusercontent.com/12782558/212848161-5e783dd6-11e8-4fe0-bbba-39ffb77730be.png"></a>
 
+- **\[2023.12.10\]** 我们开源了多模评测框架 [VLMEvalKit](https://github.com/open-compass/VLMEvalKit)，目前已支持 20+ 个多模态大模型与包括 MMBench 系列在内的 7 个多模态评测集. 🔥🔥🔥.
 - **\[2023.12.10\]** 我们已经支持了Mistral AI的MoE模型 **Mixtral-8x7B-32K**。欢迎查阅[MixtralKit](https://github.com/open-compass/MixtralKit)以获取更多关于推理和评测的详细信息。🔥🔥🔥。
 - **\[2023.11.22\]** 我们已经支持了多个于API的模型，包括**百度、字节跳动、华为、360**。欢迎查阅[模型](https://opencompass.readthedocs.io/en/latest/user_guides/models.html)部分以获取更多详细信息。🔥🔥🔥。
 - **\[2023.11.20\]** 感谢[helloyongyang](https://github.com/helloyongyang)支持使用[LightLLM](https://github.com/ModelTC/lightllm)作为后端进行评估。欢迎查阅[使用LightLLM进行评估](https://opencompass.readthedocs.io/en/latest/advanced_guides/evaluation_lightllm.html)以获取更多详细信息。🔥🔥🔥。