[Doc] Add more tips to avoid OOM (#16765)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

docs/source/serving/offline_inference.md

@@ -28,6 +28,8 @@ Please refer to the above pages for more details about each API.
 [API Reference](/api/offline_inference/index)
 :::
 
+(configuration-options)=
+
 ## Configuration Options
 
 This section lists the most common options for running the vLLM engine.
@@ -184,6 +186,29 @@ llm = LLM(model="google/gemma-3-27b-it",
           limit_mm_per_prompt={"image": 0})
 ```
 
+#### Multi-modal processor arguments
+
+For certain models, you can adjust the multi-modal processor arguments to
+reduce the size of the processed multi-modal inputs, which in turn saves memory.
+
+Here are some examples:
+
+```python
+from vllm import LLM
+
+# Available for Qwen2-VL series models
+llm = LLM(model="Qwen/Qwen2.5-VL-3B-Instruct",
+          mm_processor_kwargs={
+              "max_pixels": 768 * 768,  # Default is 1280 * 28 * 28
+          })
+
+# Available for InternVL series models
+llm = LLM(model="OpenGVLab/InternVL2-2B",
+          mm_processor_kwargs={
+              "max_dynamic_patch": 4,  # Default is 12
+          })
+```
+
 ### Performance optimization and tuning
 
 You can potentially improve the performance of vLLM by finetuning various options.