diff --git a/Dockerfile b/Dockerfile
index e83c220c6..8f1e00b09 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -15,7 +15,7 @@ ENV USE_CUDA=1 \
 ARG MAX_JOBS=90                       
 ENV DEBIAN_FRONTEND=noninteractive \
     PYTHONUNBUFFERED=1 LANG=C.UTF-8 LC_ALL=C.UTF-8 \
-    TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;8.9;9.0"
+    TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9"
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
       python3 python3-dev python3-pip python3-distutils git cmake ninja-build \
@@ -27,6 +27,10 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
 
 RUN python3 -m pip install --no-cache-dir numpy requests packaging build
 
+# 在 PyTorch 要求cmake >=3.27,ubuntu 22.04默认是cmake 3.22.1，所以现在需要安装新的：
+RUN python3 -m pip install --no-cache-dir "cmake>=3.29,<4.0" "ninja>=1.11" && \
+    cmake --version && ninja --version
+
 WORKDIR /opt
 # RUN git clone --recursive -b v2.8.0 https://github.com/pytorch/pytorch.git
 COPY ./pytorch_2.8.0/ /opt/pytorch
@@ -42,7 +46,7 @@ RUN echo "Building PyTorch with USE_DISTRIBUTED=$USE_DISTRIBUTED" && \
 ARG CUDA_VERSION=12.6.1
 FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 AS builder-extras
 
-ENV TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;8.9"
+ENV TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9"
 ENV DEBIAN_FRONTEND=noninteractive PYTHONUNBUFFERED=1 LANG=C.UTF-8 LC_ALL=C.UTF-8
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
@@ -54,6 +58,10 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
       curl xz-utils \
     && python3 -m pip install --no-cache-dir --upgrade pip wheel setuptools
 
+# for torch vision以及sglang 0.5.2：
+RUN python3 -m pip install --no-cache-dir "cmake>=3.29,<4.0" "ninja>=1.11" && \
+    cmake --version && ninja --version
+
 # ── 安装自编 torch 轮子 ──────────────────────────────────────────────────────
 COPY --from=builder-torch /opt/pytorch/dist /tmp/torch_dist
 RUN set -e && \
@@ -83,7 +91,7 @@ WORKDIR /opt/flashinfer
 
 
 # 覆盖你的目标算力：3090=8.6，4090=8.9，H100=9.0a；可按需增/减
-ENV FLASHINFER_CUDA_ARCH_LIST="7.5 8.0 8.6 8.9"
+ENV FLASHINFER_CUDA_ARCH_LIST="8.0;8.6;8.9"
 
 # 先做 AOT 预编译，再直接打 wheel（不隔离，使用同一份自编 torch）
 RUN python3 -m pip install --no-cache-dir numpy requests build "cuda-python>=12.0,<13" "nvidia-nvshmem-cu12" ninja pynvml && \