Update README (#13326)

README.md

@@ -16,7 +16,7 @@
 | [**Documentation**](https://docs.sglang.ai/)
 | [**Join Slack**](https://slack.sglang.ai/)
 | [**Join Bi-Weekly Development Meeting**](https://meeting.sglang.ai/)
-| [**Roadmap**](https://github.com/sgl-project/sglang/issues/7736)
+| [**Roadmap**](https://github.com/sgl-project/sglang/issues/12780)
 | [**Slides**](https://github.com/sgl-project/sgl-learning-materials?tab=readme-ov-file#slides) |
 
 ## News
@@ -71,7 +71,7 @@ Its core features include:
 Learn more in the release blogs: [v0.2 blog](https://lmsys.org/blog/2024-07-25-sglang-llama3/), [v0.3 blog](https://lmsys.org/blog/2024-09-04-sglang-v0-3/), [v0.4 blog](https://lmsys.org/blog/2024-12-04-sglang-v0-4/), [Large-scale expert parallelism](https://lmsys.org/blog/2025-05-05-large-scale-ep/).
 
 ## Roadmap
-[Development Roadmap (2025 H2)](https://github.com/sgl-project/sglang/issues/7736)
+[Development Roadmap (2025 Q4)](https://github.com/sgl-project/sglang/issues/12780)
 
 ## Adoption and Sponsorship
 SGLang has been deployed at large scale, generating trillions of tokens in production each day. It is trusted and adopted by a wide range of leading enterprises and institutions, including xAI, AMD, NVIDIA, Intel, LinkedIn, Cursor, Oracle Cloud, Google Cloud, Microsoft Azure, AWS, Atlas Cloud, Voltage Park, Nebius, DataCrunch, Novita, InnoMatrix, MIT, UCLA, the University of Washington, Stanford, UC Berkeley, Tsinghua University, Jam & Tea Studios, Baseten, and other major technology organizations across North America and Asia. As an open-source LLM inference engine, SGLang has become the de facto industry standard, with deployments running on over 300,000 GPUs worldwide.