[Doc] Update CPU doc (#20676)

Signed-off-by: jiang1.li <jiang1.li@intel.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

docs/getting_started/installation/cpu/x86.inc.md

@@ -1,19 +1,15 @@
 # --8<-- [start:installation]
 
-vLLM initially supports basic model inferencing and serving on x86 CPU platform, with data types FP32, FP16 and BF16.
-
-!!! warning
-    There are no pre-built wheels or images for this device, so you must build vLLM from source.
+vLLM supports basic model inferencing and serving on x86 CPU platform, with data types FP32, FP16 and BF16.
 
 # --8<-- [end:installation]
 # --8<-- [start:requirements]
 
 - OS: Linux
-- Compiler: `gcc/g++ >= 12.3.0` (optional, recommended)
-- Instruction Set Architecture (ISA): AVX512 (optional, recommended)
+- CPU flags: `avx512f`, `avx512_bf16` (Optional), `avx512_vnni` (Optional)
 
 !!! tip
-    [Intel Extension for PyTorch (IPEX)](https://github.com/intel/intel-extension-for-pytorch) extends PyTorch with up-to-date features optimizations for an extra performance boost on Intel hardware.
+    Use `lscpu` to check the CPU flags.
 
 # --8<-- [end:requirements]
 # --8<-- [start:set-up-using-python]
@@ -26,18 +22,37 @@ vLLM initially supports basic model inferencing and serving on x86 CPU platform,
 
 --8<-- "docs/getting_started/installation/cpu/build.inc.md"
 
-!!! note
-    - AVX512_BF16 is an extension ISA provides native BF16 data type conversion and vector product instructions, which brings some performance improvement compared with pure AVX512. The CPU backend build script will check the host CPU flags to determine whether to enable AVX512_BF16.
-    - If you want to force enable AVX512_BF16 for the cross-compilation, please set environment variable `VLLM_CPU_AVX512BF16=1` before the building.
-
 # --8<-- [end:build-wheel-from-source]
 # --8<-- [start:pre-built-images]
 
-See [https://gallery.ecr.aws/q9t5s3a7/vllm-cpu-release-repo](https://gallery.ecr.aws/q9t5s3a7/vllm-cpu-release-repo)
+[https://gallery.ecr.aws/q9t5s3a7/vllm-cpu-release-repo](https://gallery.ecr.aws/q9t5s3a7/vllm-cpu-release-repo)
+
+!!! warning
+    If deploying the pre-built images on machines only contain `avx512f`, `Illegal instruction` error may be raised. It is recommended to build images for these machines with `--build-arg VLLM_CPU_AVX512BF16=false` and `--build-arg VLLM_CPU_AVX512VNNI=false`.
 
 # --8<-- [end:pre-built-images]
 # --8<-- [start:build-image-from-source]
 
+```bash
+docker build -f docker/Dockerfile.cpu \
+        --build-arg VLLM_CPU_AVX512BF16=false (default)|true \
+        --build-arg VLLM_CPU_AVX512VNNI=false (default)|true \
+        --tag vllm-cpu-env \
+        --target vllm-openai .
+
+# Launching OpenAI server
+docker run --rm \
+            --privileged=true \
+            --shm-size=4g \
+            -p 8000:8000 \
+            -e VLLM_CPU_KVCACHE_SPACE=<KV cache space> \
+            -e VLLM_CPU_OMP_THREADS_BIND=<CPU cores for inference> \
+            vllm-cpu-env \
+            --model=meta-llama/Llama-3.2-1B-Instruct \
+            --dtype=bfloat16 \
+            other vLLM OpenAI server arguments
+```
+
 # --8<-- [end:build-image-from-source]
 # --8<-- [start:extra-information]
 # --8<-- [end:extra-information]