Update README.md

- Add KTransformers (SGLang + KT-Kernel) as a deployment option for GLM-5 in the model README
- Include environment setup instructions (SGLang, KT-Kernel installation) in the "Prepare environment" section

README.md

@@ -73,14 +73,14 @@ See footnote for more evaluation details.
 
 ### Prepare environment
 
-vLLM, SGLang, and xLLM all support local deployment of GLM-5. A simple deployment guide is provided here.
+vLLM, SGLang, KTransformers, and xLLM all support local deployment of GLM-5. A simple deployment guide is provided here.
 
 + vLLM
 
     Using Docker as:
 
     ```shell
-    docker pull vllm/vllm-openai:nightly 
+    docker pull vllm/vllm-openai:nightly
     ```
 
     or using pip:
@@ -103,6 +103,24 @@ vLLM, SGLang, and xLLM all support local deployment of GLM-5. A simple deploymen
     docker pull lmsysorg/sglang:glm5-blackwell # For Blackwell GPU
     ```
 
++ KTransformers (SGLang + KT-Kernel, CPU-GPU heterogeneous inference)
+
+    Install SGLang:
+
+    ```bash
+    git clone https://github.com/kvcache-ai/sglang.git
+    cd sglang
+    pip install -e "python[all]"
+    ```
+
+    Install KT-Kernel:
+
+    ```bash
+    git clone https://github.com/kvcache-ai/ktransformers.git
+    git submodule update --init --recursive
+    cd kt-kernel && ./install.sh
+    ```
+
 ### Deploy
 
 + vLLM
@@ -136,9 +154,43 @@ vLLM, SGLang, and xLLM all support local deployment of GLM-5. A simple deploymen
       --mem-fraction-static 0.85 \
       --served-model-name glm-5-fp8
     ```
-  
+
     Check the [sglang cookbook](https://cookbook.sglang.io/autoregressive/GLM/GLM-5) for more details.
 
++ KTransformers (SGLang + KT-Kernel)
+
+    ```bash
+    export PYTORCH_ALLOC_CONF=expandable_segments:True
+    export SGLANG_ENABLE_JIT_DEEPGEMM=0
+
+    python -m sglang.launch_server \
+      --host 0.0.0.0 \
+      --port 30000 \
+      --model zai-org/GLM-5 \
+      --kt-weight-path /path/to/GLM-5 \
+      --kt-cpuinfer 96 \
+      --kt-threadpool-count 2 \
+      --kt-num-gpu-experts 10 \
+      --kt-method BF16 \
+      --kt-gpu-prefill-token-threshold 1024 \
+      --kt-enable-dynamic-expert-update \
+      --kt-expert-placement-strategy uniform \
+      --trust-remote-code \
+      --mem-fraction-static 0.75 \
+      --served-model-name GLM5 \
+      --enable-mixed-chunk \
+      --tensor-parallel-size 8 \
+      --enable-p2p-check \
+      --disable-shared-experts-fusion \
+      --chunked-prefill-size 16384 \
+      --max-running-requests 4 \
+      --max-total-tokens 128000 \
+      --attention-backend flashinfer \
+      --watchdog-timeout 3000
+    ```
+
+    Check the [KTransformers GLM-5 tutorial](https://github.com/kvcache-ai/ktransformers/blob/main/doc/en/kt-kernel/GLM-5-Tutorial.md) for more details.
+
 + xLLM and other Ascend NPU
 
     Please check the deployment guide [here](https://github.com/zai-org/GLM-5/blob/main/example/ascend.md).