text: Title: [Feature] enable SGLang custom all reduce by default
  Body: ### Checklist
  
  - [ ] 1. If the issue you raised is not a feature but a question, please raise a discussion at https://github.com/sgl-project/sglang/discussions/new/choose Otherwise, it will be closed.
  - [ ] 2. Please use English, otherwise it will be closed.
  
  ### Motivation
  
  We need community users to help test these cases. After confirming that there are no issues, we will default to using the custom all reduce implemented in SGLang. You can reply with your test results below this issue. Thanks!
  
  **GPU Hardware Options**:
  - H100/H200/H20/H800/A100
  
  **Model Configurations with Tensor Parallelism (TP) Settings**:
  - Llama 8B with TP 1/2/4/8
  - Llama 70B with TP 4/8
  - Qwen 7B with TP 1/2/4/8
  - Qwen 32B with TP 4/8
  - DeepSeek V3 with TP 8/16
  
  **Environment Variables**:
  ```
  export USE_VLLM_CUSTOM_ALLREDUCE=0
  export USE_VLLM_CUSTOM_ALLREDUCE=1
  ```
  
  **Benchmarking Commands**:
  ```bash
  python3 -m sglang.bench_one_batch --model-path model --batch-size --input 128 --output 8
  python3 -m sglang.bench_serving --backend sglang
  ```
  
  ### Related resources
  
  _No response_