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π Check out the GLM-4.6 <a href="https://z.ai/blog/glm-4.6" target="_blank">technical blog</a>, <a href="https://arxiv.org/abs/2508.06471" target="_blank">technical report(GLM-4.5)</a>, and <a href="https://zhipu-ai.feishu.cn/wiki/Gv3swM0Yci7w7Zke9E0crhU7n7D" target="_blank">Zhipu AI technical documentation</a>.
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π Use GLM-4.6 API services on <a href="https://docs.z.ai/guides/llm/glm-4.6">Z.ai API Platform
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π One click to <a href="https://chat.z.ai">GLM-4.6</a>.
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## Model Introduction
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Compared with GLM-4.5, **GLM-4.6** brings several key improvements:
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## Inference
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**
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<br>
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π Check out the GLM-4.6 <a href="https://z.ai/blog/glm-4.6" target="_blank">technical blog</a>, <a href="https://arxiv.org/abs/2508.06471" target="_blank">technical report(GLM-4.5)</a>, and <a href="https://zhipu-ai.feishu.cn/wiki/Gv3swM0Yci7w7Zke9E0crhU7n7D" target="_blank">Zhipu AI technical documentation</a>.
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π Use GLM-4.6 API services on <a href="https://docs.z.ai/guides/llm/glm-4.6">Z.ai API Platform. </a>
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<br>
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π One click to <a href="https://chat.z.ai">GLM-4.6</a>.
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</p>
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## Model Introduction
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Compared with GLM-4.5, **GLM-4.6** brings several key improvements:
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## Inference
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**Both GLM-4.5 and GLM-4.6 use the same inference method.**
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you can check our [github](https://github.com/zai-org/GLM-4.5) for more detail.
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## Recommended Evaluation Parameters
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For general evaluations, we recommend using a **sampling temperature of 1.0**.
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For **code-related evaluation tasks** (such as LCB), it is further recommended to set:
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- `top_p = 0.95`
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- `top_k = 40`
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