diff --git a/marker/processors/image_to_text.py b/marker/processors/image_to_text.py
new file mode 100644
index 000000000..3bc7d9a6f
--- /dev/null
+++ b/marker/processors/image_to_text.py
@@ -0,0 +1,120 @@
+from __future__ import annotations
+
+import base64
+import io
+from copy import deepcopy
+from typing import Optional, List
+
+import markdown2
+import requests
+from PIL import Image
+
+from marker.processors import BaseProcessor
+from marker.schema import BlockTypes
+from marker.schema.document import Document
+from marker.schema.registry import get_block_class
+
+
+class ImageToTextProcessor(BaseProcessor):
+    """Replace image blocks with markdown descriptions."""
+
+    block_types = (BlockTypes.Picture, BlockTypes.Figure)
+
+    def __init__(self, config: Optional[dict] = None) -> None:
+        super().__init__(config)
+        if config is None:
+            config = {}
+        self.ollama_url = config.get("ollama_url", "http://localhost:11434").rstrip("/")
+        self.ollama_model = config.get("ollama_model", "llama3.2-vision:11b")
+        self.vision_prompt = config.get(
+            "vision_prompt",
+            "Describe this image precisely in technical terms. Focus on diagrams, code, text, and technical content.",
+        )
+
+    def process_image_to_text(self, image: Image.Image) -> str:
+        """Convert an image to a markdown description using the Ollama service."""
+        try:
+            buffer = io.BytesIO()
+            image.save(buffer, format="PNG")
+            image_b64 = base64.b64encode(buffer.getvalue()).decode()
+            payload = {
+                "model": self.ollama_model,
+                "prompt": self.vision_prompt,
+                "images": [image_b64],
+                "stream": False,
+            }
+            resp = requests.post(f"{self.ollama_url}/api/generate", json=payload, timeout=120)
+            resp.raise_for_status()
+            result = resp.json()
+            description = result.get("response", "").strip()
+            return f"[Image Description: {description}]"
+        except Exception as e:  # pragma: no cover - external service
+            return f"[Image processing failed: {str(e)}]"
+
+    def __call__(self, document: Document) -> None:
+        TextClass = get_block_class(BlockTypes.Text)
+        for page in document.pages:
+            for block in list(page.contained_blocks(document, self.block_types)):
+                try:
+                    image = block.get_image(document, highres=True)
+                    if image is None:
+                        continue
+                    markdown_text = self.process_image_to_text(image)
+                    html = markdown2.markdown(markdown_text, extras=["tables"])
+                    new_block = TextClass(
+                        polygon=deepcopy(block.polygon),
+                        page_id=block.page_id,
+                        structure=deepcopy(block.structure),
+                        text_extraction_method=block.text_extraction_method,
+                        source="processor",
+                        top_k=block.top_k,
+                        metadata=block.metadata,
+                        html=html,
+                    )
+                    page.replace_block(block, new_block)
+                except Exception:
+                    continue
+
+
+
+def create_converter_with_image_to_text(
+    config: Optional[dict] = None,
+    ollama_url: str = "http://localhost:11434",
+    ollama_model: str = "llama3.2-vision:11b",
+    vision_prompt: str = (
+        "Describe this image precisely in technical terms. Focus on diagrams, code, text, and technical content."
+    ),
+) -> "PdfConverter":
+    """Return a PdfConverter that applies ImageToTextProcessor."""
+    from marker.converters.pdf import PdfConverter
+    from marker.models import create_model_dict
+    from marker.config.parser import ConfigParser
+    from marker.util import classes_to_strings
+
+    if config is None:
+        config = {"extract_images": True, "output_dir": "output"}
+
+    if "page_range" in config and isinstance(config["page_range"], list):
+        config["page_range"] = ",".join(str(p) for p in config["page_range"])
+
+    # Store ollama params so the processor can access them
+    config.update({
+        "ollama_url": ollama_url,
+        "ollama_model": ollama_model,
+        "vision_prompt": vision_prompt,
+    })
+
+    config_parser = ConfigParser(config)
+    processors = config_parser.get_processors()
+    if processors is None:
+        processors = classes_to_strings(list(PdfConverter.default_processors) + [ImageToTextProcessor])
+    else:
+        processors.append("marker.processors.image_to_text.ImageToTextProcessor")
+
+    converter = PdfConverter(
+        artifact_dict=create_model_dict(),
+        config=config_parser.generate_config_dict(),
+        processor_list=processors,
+        renderer=config_parser.get_renderer(),
+    )
+    return converter