diff --git a/README.md b/README.md
index e47d6de50..7ca938bd1 100644
--- a/README.md
+++ b/README.md
@@ -337,10 +337,9 @@ inference on physical Blackwell hardware.
 
 ## What's new
 
-- **FunASR 1.4.11** is the current PyPI release. It improves readable multilingual subtitles while preserving real model timestamps. Install with `python -m pip install -U "funasr==1.4.11"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
-- **MOSS-Transcribe-Diarize integration** adds long-form ASR, timestamps, and anonymous speaker labels in one generation, without an external VAD or speaker pipeline. FunASR supports local Transformers and existing vLLM/SGLang services; FunClip can export speaker-aware SRT and clips. [Deployment guide ->](./docs/moss_transcribe_diarize.md)
-- **llama.cpp runtime v0.2.6** provides verified prebuilt archives for ten Linux, macOS, and Windows targets, including dedicated Windows CUDA packages for RTX 30/40 and RTX 50 GPUs. [Download matrix ->](https://www.funasr.com/en/deploy/llama-cpp.html)
-- **Realtime serving is faster and more resilient**: compatible WebSocket sessions are batched instead of serialized, and queued decoding no longer closes healthy sessions by default. On the H100 regression workload, 12-client STOP p95 fell from 19.8 s to 0.4 s. [Production guide ->](./docs/vllm_guide.md)
+- **MOSS-Transcribe-Diarize** brings long-form ASR, timestamps, and anonymous speaker labels to FunASR services, Docker, Kubernetes, vLLM/SGLang workflows, and FunClip. [Deploy MOSS ->](./docs/moss_transcribe_diarize.md)
+- **FunASR 1.4.11** is the current PyPI release, with more readable multilingual subtitles and preserved model timestamps. [Install or upgrade ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
+- **Production deployment** now includes faster, more resilient realtime serving and verified llama.cpp archives for ten Linux, macOS, and Windows targets. [GPU services ->](./docs/vllm_guide.md) · [CPU/edge packages ->](https://www.funasr.com/en/deploy/llama-cpp.html)
 
 > See [GitHub Releases](https://github.com/modelscope/FunASR/releases) for the complete changelog and downloadable assets.
 
diff --git a/README_ja.md b/README_ja.md
index b64f5ff36..ef80af4ca 100644
--- a/README_ja.md
+++ b/README_ja.md
@@ -99,10 +99,9 @@ Whisper は単一モデルですが、**FunASR はツールキット**です—
 
 ## 最新情報
 
-- **FunASR 1.4.11** は現在の PyPI 安定版です。実際のモデル timestamp を保持しながら、多言語字幕の可読性を改善しました。更新：`python -m pip install -U "funasr==1.4.11"`。[Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
-- **MOSS-Transcribe-Diarize 連携**では、長時間音声の ASR、timestamp、匿名 speaker label を 1 回の生成で処理でき、外部 VAD や speaker pipeline は不要です。FunASR は local Transformers と既存の vLLM/SGLang service に対応し、FunClip は speaker 付き SRT と clip を出力できます。[Deployment guide ->](./docs/moss_transcribe_diarize.md)
-- **llama.cpp runtime v0.2.6** は Linux、macOS、Windows の 10 target 向け検証済み archive を提供し、RTX 30/40 と RTX 50 向け Windows CUDA package を分けて用意しています。[Download matrix ->](https://www.funasr.com/en/deploy/llama-cpp.html) · [Release ->](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.6)
-- **Realtime serving の高速化と安定化**：互換 WebSocket session を直列処理せず batch 化し、decode queue によって正常な session を default で切断しないようにしました。H100 regression workload では 12-client STOP p95 が 19.8 秒から 0.4 秒に短縮しました。[Production guide ->](./docs/vllm_guide.md)
+- **MOSS-Transcribe-Diarize** を FunASR service、Docker、Kubernetes、vLLM/SGLang workflow、FunClip に統合し、長時間 ASR、timestamp、匿名 speaker label を一度に処理できます。[MOSS をデプロイ ->](./docs/moss_transcribe_diarize.md)
+- **FunASR 1.4.11** は現在の PyPI 安定版で、多言語字幕の可読性を改善しながらモデル本来の timestamp を保持します。[Install / upgrade ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
+- **Production deployment** に、より高速で安定した realtime serving と、Linux、macOS、Windows の 10 target 向け llama.cpp package を追加しました。[GPU service ->](./docs/vllm_guide.md) · [CPU / edge package ->](https://www.funasr.com/en/deploy/llama-cpp.html)
 
 > 完全な変更履歴と download asset は [GitHub Releases](https://github.com/modelscope/FunASR/releases) を参照してください。
 
diff --git a/README_ko.md b/README_ko.md
index ea57f313e..8bd3724e4 100644
--- a/README_ko.md
+++ b/README_ko.md
@@ -99,10 +99,9 @@ Whisper는 단일 모델이지만, **FunASR는 툴킷**입니다. 용도에 맞
 
 ## 최신 소식
 
-- **FunASR 1.4.11**은 현재 PyPI 안정 버전입니다. 실제 모델 timestamp를 유지하면서 다국어 자막의 가독성을 개선했습니다. 업데이트: `python -m pip install -U "funasr==1.4.11"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
-- **MOSS-Transcribe-Diarize 연동**은 긴 오디오의 ASR, timestamp, 익명 speaker label을 한 번의 생성으로 처리하므로 외부 VAD 또는 speaker pipeline이 필요하지 않습니다. FunASR은 local Transformers와 기존 vLLM/SGLang service를 지원하고, FunClip은 speaker별 SRT와 clip을 내보낼 수 있습니다. [Deployment guide ->](./docs/moss_transcribe_diarize.md)
-- **llama.cpp runtime v0.2.6**은 Linux, macOS, Windows 10개 target용 검증된 archive를 제공하며 RTX 30/40 및 RTX 50용 Windows CUDA package를 별도로 제공합니다. [Download matrix ->](https://www.funasr.com/en/deploy/llama-cpp.html) · [Release ->](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.6)
-- **Realtime serving 성능과 안정성 개선**: 호환 WebSocket session을 직렬 처리하지 않고 batch 처리하며, decode queue 때문에 정상 session을 기본적으로 종료하지 않습니다. H100 regression workload에서 12-client STOP p95가 19.8초에서 0.4초로 줄었습니다. [Production guide ->](./docs/vllm_guide.md)
+- **MOSS-Transcribe-Diarize**를 FunASR service, Docker, Kubernetes, vLLM/SGLang workflow, FunClip에 통합해 긴 오디오 ASR, timestamp, 익명 speaker label을 한 번에 처리합니다. [MOSS 배포 ->](./docs/moss_transcribe_diarize.md)
+- **FunASR 1.4.11**은 현재 PyPI 안정 버전으로, 모델의 실제 timestamp를 유지하면서 다국어 자막 가독성을 개선합니다. [Install / upgrade ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
+- **Production deployment**에 더 빠르고 안정적인 realtime serving과 Linux, macOS, Windows 10개 target용 llama.cpp package를 추가했습니다. [GPU service ->](./docs/vllm_guide.md) · [CPU / edge package ->](https://www.funasr.com/en/deploy/llama-cpp.html)
 
 > 전체 변경 기록과 download asset은 [GitHub Releases](https://github.com/modelscope/FunASR/releases)에서 확인할 수 있습니다.
 
diff --git a/README_zh.md b/README_zh.md
index d448559cd..4e8daf06a 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -149,10 +149,9 @@ Whisper 是单个模型，**FunASR 是一个工具箱**——按场景挑模型
 
 ## 最新动态
 
-- **FunASR 1.4.11** 是当前 PyPI 稳定版，重点改善多语言可读字幕，并保留模型真实时间戳。升级命令：`python -m pip install -U "funasr==1.4.11"`。[发布页 ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
-- **MOSS-Transcribe-Diarize 已接入生态**：一次生成同时完成长音频转写、时间戳和匿名说话人标签，无需外挂 VAD 或说话人流水线。FunASR 支持本地 Transformers 及已有 vLLM/SGLang 服务，FunClip 可导出带说话人的 SRT 和片段。[部署指南 ->](./docs/moss_transcribe_diarize_zh.md)
-- **llama.cpp runtime v0.2.6** 提供覆盖 Linux、macOS、Windows 十种目标的已验证预编译包，并为 RTX 30/40 与 RTX 50 显卡分别提供 Windows CUDA 包。[下载矩阵 ->](https://www.funasr.com/deploy/llama-cpp.html)
-- **实时服务更快、更稳定**：兼容的 WebSocket 会话改为批处理，排队解码也不再默认误关健康连接。在 H100 回归负载下，12 路客户端 STOP p95 从 19.8 秒降至 0.4 秒。[生产部署指南 ->](./docs/vllm_guide_zh.md)
+- **MOSS-Transcribe-Diarize** 已接入 FunASR 服务、Docker、Kubernetes、vLLM/SGLang 工作流和 FunClip，一次完成长音频转写、时间戳与匿名说话人标注。[部署 MOSS ->](./docs/moss_transcribe_diarize_zh.md)
+- **FunASR 1.4.11** 是当前 PyPI 稳定版，重点改善多语言可读字幕并保留模型真实时间戳。[安装或升级 ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.11)
+- **工业部署** 新增更快、更稳定的实时服务，以及覆盖 Linux、macOS、Windows 十种目标的 llama.cpp 预编译包。[GPU 服务 ->](./docs/vllm_guide_zh.md) · [CPU/端侧包 ->](https://www.funasr.com/deploy/llama-cpp.html)
 
 > 完整改动记录和可下载资产请查看 [GitHub Releases](https://github.com/modelscope/FunASR/releases)。