diff --git a/deepdoc/parser/mineru_parser.py b/deepdoc/parser/mineru_parser.py
index b369f9122a..2c35ead98c 100644
--- a/deepdoc/parser/mineru_parser.py
+++ b/deepdoc/parser/mineru_parser.py
@@ -644,6 +644,12 @@ class MinerUParser(RAGFlowPdfParser):
                 case MinerUContentType.IMAGE:
                     section = "".join(output.get("image_caption", [])) + "\n" + "".join(
                         output.get("image_footnote", []))
+                    # If a vision model enriched this image with a semantic
+                    # description (see _enhance_images_with_vlm), embed it in
+                    # the chunk so it becomes searchable / retrievable.
+                    vlm_description = (output.get("vlm_description") or "").strip()
+                    if vlm_description:
+                        section = (section.strip("\n") + "\n" + vlm_description).strip("\n") if section.strip() else vlm_description
                 case MinerUContentType.EQUATION:
                     section = output.get("text", "")
                 case MinerUContentType.CODE:
@@ -664,6 +670,49 @@ class MinerUParser(RAGFlowPdfParser):
     def _transfer_to_tables(self, outputs: list[dict[str, Any]]):
         return []
 
+    def _enhance_images_with_vlm(self, outputs: list[dict[str, Any]], vision_model, callback: Optional[Callable] = None):
+        """Generate semantic descriptions for image blocks via the tenant's
+        IMAGE2TEXT model, mirroring deepdoc's VisionFigureParser. Each
+        IMAGE block with a readable img_path gets a ``vlm_description``
+        field that ``_transfer_to_sections`` then folds into the chunk
+        text — closing issue #14869.
+        """
+        from concurrent.futures import ThreadPoolExecutor, as_completed
+        from rag.app.picture import vision_llm_chunk
+        from rag.prompts.generator import vision_llm_figure_describe_prompt
+
+        image_jobs = [
+            (idx, item)
+            for idx, item in enumerate(outputs)
+            if item.get("type") == MinerUContentType.IMAGE
+            and item.get("img_path")
+            and os.path.exists(item["img_path"])
+        ]
+        if not image_jobs:
+            return
+
+        if callback:
+            callback(0.78, f"[MinerU] Generating VLM descriptions for {len(image_jobs)} images...")
+
+        prompt = vision_llm_figure_describe_prompt()
+
+        def worker(idx, item):
+            try:
+                with Image.open(item["img_path"]) as img:
+                    img.load()
+                    desc = vision_llm_chunk(binary=img, vision_model=vision_model, prompt=prompt)
+                return idx, (desc or "").strip()
+            except Exception as e:
+                logging.warning(f"[MinerU] VLM description failed for image #{idx}: {e}")
+                return idx, ""
+
+        with ThreadPoolExecutor(max_workers=10) as executor:
+            futures = [executor.submit(worker, idx, item) for idx, item in image_jobs]
+            for fut in as_completed(futures):
+                idx, desc = fut.result()
+                if desc:
+                    outputs[idx]["vlm_description"] = desc
+
     def parse_pdf(
             self,
             filepath: str | PathLike[str],
@@ -744,6 +793,13 @@ class MinerUParser(RAGFlowPdfParser):
             if callback:
                 callback(0.75, f"[MinerU] Parsed {len(outputs)} blocks from PDF.")
 
+            vision_model = kwargs.get("vision_model")
+            if vision_model is not None:
+                try:
+                    self._enhance_images_with_vlm(outputs, vision_model, callback=callback)
+                except Exception as e:
+                    self.logger.warning(f"[MinerU] VLM image enhancement failed: {e}. Continuing without descriptions.")
+
             return self._transfer_to_sections(outputs, parse_method), self._transfer_to_tables(outputs)
         finally:
             if temp_pdf and temp_pdf.exists():
diff --git a/rag/app/naive.py b/rag/app/naive.py
index f91e2a8f94..7bf4743e7d 100644
--- a/rag/app/naive.py
+++ b/rag/app/naive.py
@@ -131,6 +131,19 @@ def by_mineru(
                 ocr_model_config = get_model_config_by_type_and_name(tenant_id, LLMType.OCR, mineru_llm_name)
                 ocr_model = LLMBundle(tenant_id=tenant_id, model_config=ocr_model_config, lang=lang)
                 pdf_parser = ocr_model.mdl
+
+                # Closes #14869: when the tenant has an IMAGE2TEXT model
+                # configured, let the MinerU parser enrich image chunks with
+                # VLM-generated semantic descriptions (parity with deepdoc's
+                # VisionFigureParser). Best-effort — fall back silently if
+                # no vision model is available.
+                if "vision_model" not in kwargs:
+                    try:
+                        vision_model_config = get_tenant_default_model_by_type(tenant_id, LLMType.IMAGE2TEXT)
+                        kwargs["vision_model"] = LLMBundle(tenant_id=tenant_id, model_config=vision_model_config, lang=lang)
+                    except Exception as vlm_err:
+                        logging.info(f"[MinerU] no IMAGE2TEXT model for tenant; skipping image VLM enhancement: {vlm_err}")
+
                 sections, tables = pdf_parser.parse_pdf(
                     filepath=filename,
                     binary=binary,