diff --git a/homelab-ai-bot/llm.py b/homelab-ai-bot/llm.py
index 17f883594..397d2f98f 100644
--- a/homelab-ai-bot/llm.py
+++ b/homelab-ai-bot/llm.py
@@ -341,7 +341,7 @@ def ask(question: str, context: str) -> str:
         return f"LLM-Fehler: {e}"
 
 
-def ask_with_tools(question: str, tool_handlers: dict, session_id: str = None, document_mode: bool = False) -> str:
+def ask_with_tools(question: str, tool_handlers: dict, session_id: str = None, document_mode: bool = False, model_override: str = None) -> str:
     """Freitext-Frage mit automatischem Routing und Tool-Calling.
 
     Routing:
@@ -573,11 +573,12 @@ def ask_with_tools(question: str, tool_handlers: dict, session_id: str = None, d
             return f"Online-Suche Fehler: {e}"
 
     # --- Lokal: Tool-Calling mit allen Tools ---
+    local_model = model_override or MODEL_LOCAL
     passthrough_result = None
 
     try:
         for _round in range(MAX_TOOL_ROUNDS):
-            data = _call_api(messages, api_key, use_tools=True, model=MODEL_LOCAL)
+            data = _call_api(messages, api_key, use_tools=True, model=local_model)
             choice = data["choices"][0]
             msg = choice["message"]
 
@@ -623,7 +624,7 @@ def ask_with_tools(question: str, tool_handlers: dict, session_id: str = None, d
 
         if passthrough_result:
             return passthrough_result
-        data = _call_api(messages, api_key, use_tools=False, model=MODEL_LOCAL)
+        data = _call_api(messages, api_key, use_tools=False, model=local_model)
         return data["choices"][0]["message"]["content"]
 
     except Exception as e:
diff --git a/homelab-ai-bot/telegram_bot.py b/homelab-ai-bot/telegram_bot.py
index 74f03a502..b8d6540f9 100644
--- a/homelab-ai-bot/telegram_bot.py
+++ b/homelab-ai-bot/telegram_bot.py
@@ -1016,6 +1016,28 @@ async def _send_daily_forecast(job_context):
             session_id=None,
             document_mode=False,
         )
+        if (analysis or "").startswith(("LLM-Fehler:", "Vision-LLM-Fehler:")):
+            log.error("Systemvorhersage LLM-Fehler: %s", analysis[:200])
+            analysis = await asyncio.to_thread(
+                llm.ask_with_tools,
+                prompt,
+                handlers,
+                session_id=None,
+                document_mode=False,
+                model_override=llm.MODEL_VISION,
+            )
+        if (analysis or "").startswith(("LLM-Fehler:", "Vision-LLM-Fehler:")):
+            await bot.send_message(
+                chat_id=CHAT_ID,
+                text=(
+                    "🔭 *Taegliche Systemvorhersage*\n\n"
+                    "⚠️ Analyse fehlgeschlagen (OpenRouter). "
+                    "Bitte spaeter erneut versuchen."
+                ),
+                parse_mode="Markdown",
+            )
+            log.error("Systemvorhersage endgueltig fehlgeschlagen: %s", analysis[:200])
+            return
         msg = "🔭 *Taegliche Systemvorhersage*\n\n" + analysis
         await bot.send_message(chat_id=CHAT_ID, text=msg, parse_mode="Markdown")
         log.info("Taegl. Systemvorhersage gesendet")