chore(readme): update readme

Author: gufengc

README.md

@@ -64,7 +64,7 @@ We warmly welcome contributions of all kinds! For guidelines on how to get invol
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 |DeepSeek      | Deepseek     | [DeepSeek-V3.2](https://huggingface.co/deepseek-ai/DeepSeek-V3.2)<br>[DeepSeek-R1](https://huggingface.co/collections/deepseek-ai/deepseek-r1) <br>| [Deep Seek AI Launches Revolutionary Language Model](https://deepseek.ai/blog/deepseek-v32) | Deep Seek AI is proud to announce the launch of our latest language model, setting new standards in natural language processing and understanding. This breakthrough represents a significant step forward in AI technology, offering unprecedented capabilities in text generation, comprehension, and analysis. |
 |MiniMax-M2    | MiniMax AI  | [MiniMax-M2](https://huggingface.co/MiniMaxAI/MiniMax-M2)<br>[MiniMax-M2.1](https://huggingface.co/MiniMaxAI/MiniMax-M2.1)<br>[MiniMax-M2.7](https://huggingface.co/MiniMaxAI/MiniMax-M2.7) | [MiniMax M2.1: Significantly Enhanced Multi-Language Programming](https://www.minimax.io/news/minimax-m21) | MiniMax-M2.7 and MiniMax-M2.1 are enhanced sparse MoE models (about 230B parameters, 10B active) built for advanced coding and agentic workflows. They offer state-of-the-art intelligence, delivering efficient, reliable tool use and strong multi-step reasoning. |
-|GLM           | Z AI | [GLM-4.7](https://huggingface.co/zai-org/GLM-4.7) <br>[GLM-4.7-Flash](https://huggingface.co/zai-org/GLM-4.7-Flash) | [GLM-4.7: Advancing the Coding Capability](https://z.ai/blog/glm-4.7) | "GLM" is an advanced large language model series from Z AI, including GLM-4.6 and GLM-4.7. These models feature long-context support, strong coding and reasoning performance, enhanced tool-use and agent integration, and competitive results across leading open-source benchmarks. |
+|GLM           | Z AI | [GLM-5](https://huggingface.co/zai-org/GLM-5) <br>[GLM-5.1](https://huggingface.co/zai-org/GLM-5.1) | [GLM-5.1 Overview](https://docs.z.ai/guides/llm/glm-5.1) | "GLM" is an advanced large language model series from Z AI, including GLM-5 and GLM-5.1. These models feature long-context support, strong coding and reasoning performance, enhanced tool-use and agent integration, and competitive results across leading open-source benchmarks. |
 |Kimi-K2       | Moonshot AI  | [Kimi-K2](https://huggingface.co/collections/moonshotai/kimi-k2-6871243b990f2af5ba60617d) | [Kimi K2: Open Agentic Intelligence](https://moonshotai.github.io/Kimi-K2/) | "Kimi-K2" is Moonshot AI's Kimi-K2 model family, including Kimi-K2-Base, Kimi-K2-Instruct and Kimi-K2-Thinking. Kimi K2 Thinking is a state-of-the-art open-source agentic model designed for deep, step-by-step reasoning and dynamic tool use. It features native INT4 quantization and a 256k context window for fast, memory-efficient inference. Uniquely stable in long-horizon tasks, Kimi K2 enables reliable autonomous workflows with consistent performance across hundreds of tool calls.
 |Qwen          | Qwen         | [Qwen3-Next](https://huggingface.co/collections/Qwen/qwen3-next-68c25fd6838e585db8eeea9d) <br>[Qwen3](https://huggingface.co/collections/Qwen/qwen3-67dd247413f0e2e4f653967f) <br>[Qwen2.5](https://huggingface.co/collections/Qwen/qwen25-66e81a666513e518adb90d9e)| [Qwen3-Next: Towards Ultimate Training & Inference Efficiency](https://qwen.ai/blog?id=4074cca80393150c248e508aa62983f9cb7d27cd&from=research.latest-advancements-list) | The Qwen series is a family of large language models developed by Alibaba's Qwen team. It includes multiple generations such as Qwen2.5, Qwen3, and Qwen3-Next, which improve upon model architecture, efficiency, and capabilities. The models are available in various sizes and instruction-tuned versions, with support for cutting-edge features like long context and quantization. Suitable for a wide range of language tasks and open-source use cases. |
 |gpt-oss       | OpenAI       | [gpt-oss](https://huggingface.co/collections/openai/gpt-oss-68911959590a1634ba11c7a4) <br>[gpt-oss-safeguard](https://huggingface.co/collections/openai/gpt-oss-safeguard) | [Introducing gpt-oss-safeguard](https://openai.com/index/introducing-gpt-oss-safeguard/) | gpt-oss are OpenAI’s open-weight GPT models (20B & 120B). The gpt-oss-safeguard variants are reasoning-based safety classification models: developers provide their own policy at inference, and the model uses chain-of-thought to classify content and explain its reasoning. This allows flexible, policy-driven moderation in complex or evolving domains, with open weights under Apache 2.0. |