diff --git a/__init__.py b/__init__.py
index ae76efa..77164d9 100644
--- a/__init__.py
+++ b/__init__.py
@@ -12,8 +12,9 @@ from .gemini_tts import NODE_CLASS_MAPPINGS as GEMINI_TTS_MAPPINGS, NODE_DISPLAY
 from .elevenlabs_tts import NODE_CLASS_MAPPINGS as ELEVENLABS_TTS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as ELEVENLABS_TTS_DISPLAY
 from .flux2_replicate import NODE_CLASS_MAPPINGS as FLUX2_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as FLUX2_DISPLAY
 from .openai_tts import NODE_CLASS_MAPPINGS as OPENAI_TTS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as OPENAI_TTS_DISPLAY
+from .openai_node import NODE_CLASS_MAPPINGS as OPENAI_LLM_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as OPENAI_LLM_DISPLAY
 from .cleanup import NODE_CLASS_MAPPINGS as CLEANUP_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as CLEANUP_DISPLAY
 
-NODE_CLASS_MAPPINGS = {**PRO_MAPPINGS, **GEMINI_MAPPINGS, **GEMINI_DIAR_MAPPINGS, **GPT_IMAGE_MAPPINGS, **IMAGEN_IMAGE_MAPPINGS, **IMAGEN_EDIT_MAPPINGS, **VEO_MAPPINGS, **VEO_GEMINI_MAPPINGS, **GEMINI_SEGMENT_MAPPINGS, **NANO_BANANA_MAPPINGS, **GEMINI_TTS_MAPPINGS, **ELEVENLABS_TTS_MAPPINGS, **FLUX2_MAPPINGS, **OPENAI_TTS_MAPPINGS, **CLEANUP_MAPPINGS}
-NODE_DISPLAY_NAME_MAPPINGS = {**PRO_DISPLAY, **GEMINI_DISPLAY, **GEMINI_DIAR_DISPLAY, **GPT_IMAGE_DISPLAY, **IMAGEN_IMAGE_DISPLAY, **IMAGEN_EDIT_DISPLAY, **VEO_DISPLAY, **VEO_GEMINI_DISPLAY, **GEMINI_SEGMENT_DISPLAY, **NANO_BANANA_DISPLAY, **GEMINI_TTS_DISPLAY, **ELEVENLABS_TTS_DISPLAY, **FLUX2_DISPLAY, **OPENAI_TTS_DISPLAY, **CLEANUP_DISPLAY}
+NODE_CLASS_MAPPINGS = {**PRO_MAPPINGS, **GEMINI_MAPPINGS, **GEMINI_DIAR_MAPPINGS, **GPT_IMAGE_MAPPINGS, **IMAGEN_IMAGE_MAPPINGS, **IMAGEN_EDIT_MAPPINGS, **VEO_MAPPINGS, **VEO_GEMINI_MAPPINGS, **GEMINI_SEGMENT_MAPPINGS, **NANO_BANANA_MAPPINGS, **GEMINI_TTS_MAPPINGS, **ELEVENLABS_TTS_MAPPINGS, **FLUX2_MAPPINGS, **OPENAI_TTS_MAPPINGS, **OPENAI_LLM_MAPPINGS, **CLEANUP_MAPPINGS}
+NODE_DISPLAY_NAME_MAPPINGS = {**PRO_DISPLAY, **GEMINI_DISPLAY, **GEMINI_DIAR_DISPLAY, **GPT_IMAGE_DISPLAY, **IMAGEN_IMAGE_DISPLAY, **IMAGEN_EDIT_DISPLAY, **VEO_DISPLAY, **VEO_GEMINI_DISPLAY, **GEMINI_SEGMENT_DISPLAY, **NANO_BANANA_DISPLAY, **GEMINI_TTS_DISPLAY, **ELEVENLABS_TTS_DISPLAY, **FLUX2_DISPLAY, **OPENAI_TTS_DISPLAY, **OPENAI_LLM_DISPLAY, **CLEANUP_DISPLAY}
 __all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']
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diff --git a/openai_node.py b/openai_node.py
new file mode 100644
index 0000000..04a1d7b
--- /dev/null
+++ b/openai_node.py
@@ -0,0 +1,89 @@
+import os
+import io
+import base64
+import torch
+import numpy as np
+from PIL import Image
+from openai import OpenAI
+
+class OpenAILLMNode:
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "prompt": ("STRING", {"multiline": True, "default": ""}),
+                "model": (["gpt-4.1","gpt-4.1-mini","gpt-5","gpt-5.2","gpt-5-mini","gpt-5-nano","gpt-5.2-pro","o1","o3-mini"],),
+                "temperature": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 2.0, "step": 0.01}),
+                "reasoning_effort": (["low", "medium", "high"],),
+                "api_key": ("STRING", {"multiline": False, "default": ""}),
+                "max_output_tokens": ("INT", {"default": 16384, "min": 1, "max": 32768, "step": 1})
+            },
+            "optional": {
+                "system_instruction": ("STRING", {"multiline": True, "default": ""}),
+                "image": ("IMAGE",),
+            }
+        }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("response",)
+    FUNCTION = "generate"
+    CATEGORY = "text/generation"
+    
+    def generate(self, prompt, model, temperature, reasoning_effort, api_key, max_output_tokens,
+                 system_instruction="", image=None):
+        
+        if not prompt.strip():
+            raise ValueError("Prompt cannot be empty.")
+        
+        key = api_key.strip() or os.environ.get("OPENAI_API_KEY")
+        if not key:
+            raise ValueError("No API key provided.")
+        
+        client = OpenAI(api_key=key)
+        
+        # Build input content
+        if image is not None:
+            img_array = image.cpu().numpy() if isinstance(image, torch.Tensor) else image
+            if len(img_array.shape) == 4:
+                img_array = img_array[0]
+            if img_array.dtype in [np.float32, np.float64]:
+                img_array = (img_array * 255).astype(np.uint8)
+            
+            buffered = io.BytesIO()
+            Image.fromarray(img_array).save(buffered, format="PNG")
+            base64_image = base64.b64encode(buffered.getvalue()).decode("utf-8")
+            
+            input_content = [{
+                "role": "user",
+                "content": [
+                    {"type": "input_text", "text": prompt},
+                    {"type": "input_image", "image_url": f"data:image/png;base64,{base64_image}"}
+                ]
+            }]
+        else:
+            input_content = prompt
+        
+        # Build request
+        request_params = {
+            "model": model,
+            "input": input_content,
+            "temperature": temperature,
+            "max_output_tokens": max_output_tokens
+        }
+        
+        # Only add reasoning for o-series and gpt-5+ models
+        if not model.startswith("gpt-4"):
+            request_params["reasoning"] = {"effort": reasoning_effort}
+        else:
+            print(f"Skipping reasoning parameter for {model} (not supported)")
+        
+        if system_instruction.strip():
+            request_params["instructions"] = system_instruction
+        
+        response = client.responses.create(**request_params)
+        
+        return (response.output_text,)
+
+NODE_CLASS_MAPPINGS = {"OpenAILLMNode": OpenAILLMNode}
+NODE_DISPLAY_NAME_MAPPINGS = {"OpenAILLMNode": "OpenAI LLM"}
\ No newline at end of file