diff --git a/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx b/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx
index ad7c08d35..b3ecab4b1 100644
--- a/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx
+++ b/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx
@@ -21,10 +21,50 @@ import { useModal } from "@/hooks/useModal";
 import ModalWrapper from "@/components/ModalWrapper";
 import CTAButton from "@/components/lib/CTAButton";
 
+const EMBEDDERS = [
+  {
+    name: "AnythingLLM Embedder",
+    value: "native",
+    logo: AnythingLLMIcon,
+    options: (settings) => <NativeEmbeddingOptions settings={settings} />,
+    description:
+      "Use the built-in embedding engine for AnythingLLM. Zero setup!",
+  },
+  {
+    name: "OpenAI",
+    value: "openai",
+    logo: OpenAiLogo,
+    options: (settings) => <OpenAiOptions settings={settings} />,
+    description: "The standard option for most non-commercial use.",
+  },
+  {
+    name: "Azure OpenAI",
+    value: "azure",
+    logo: AzureOpenAiLogo,
+    options: (settings) => <AzureAiOptions settings={settings} />,
+    description: "The enterprise option of OpenAI hosted on Azure services.",
+  },
+  {
+    name: "Local AI",
+    value: "localai",
+    logo: LocalAiLogo,
+    options: (settings) => <LocalAiOptions settings={settings} />,
+    description: "Run embedding models locally on your own machine.",
+  },
+  {
+    name: "Ollama",
+    value: "ollama",
+    logo: OllamaLogo,
+    options: (settings) => <OllamaEmbeddingOptions settings={settings} />,
+    description: "Run embedding models locally on your own machine.",
+  },
+];
+
 export default function GeneralEmbeddingPreference() {
   const [saving, setSaving] = useState(false);
   const [hasChanges, setHasChanges] = useState(false);
   const [hasEmbeddings, setHasEmbeddings] = useState(false);
+  const [hasCachedEmbeddings, setHasCachedEmbeddings] = useState(false);
   const [settings, setSettings] = useState(null);
   const [loading, setLoading] = useState(true);
   const [searchQuery, setSearchQuery] = useState("");
@@ -34,12 +74,24 @@ export default function GeneralEmbeddingPreference() {
   const searchInputRef = useRef(null);
   const { isOpen, openModal, closeModal } = useModal();
 
+  function embedderModelChanged(formEl) {
+    try {
+      const newModel = new FormData(formEl).get("EmbeddingModelPref") ?? null;
+      if (newModel === null) return false;
+      return settings?.EmbeddingModelPref !== newModel;
+    } catch (error) {
+      console.error(error);
+    }
+    return false;
+  }
+
   const handleSubmit = async (e) => {
     e.preventDefault();
     if (
-      selectedEmbedder !== settings?.EmbeddingEngine &&
+      (selectedEmbedder !== settings?.EmbeddingEngine ||
+        embedderModelChanged(e.target)) &&
       hasChanges &&
-      hasEmbeddings
+      (hasEmbeddings || hasCachedEmbeddings)
     ) {
       openModal();
     } else {
@@ -89,50 +141,12 @@ export default function GeneralEmbeddingPreference() {
       setSettings(_settings);
       setSelectedEmbedder(_settings?.EmbeddingEngine || "native");
       setHasEmbeddings(_settings?.HasExistingEmbeddings || false);
+      setHasCachedEmbeddings(_settings?.HasCachedEmbeddings || false);
       setLoading(false);
     }
     fetchKeys();
   }, []);
 
-  const EMBEDDERS = [
-    {
-      name: "AnythingLLM Embedder",
-      value: "native",
-      logo: AnythingLLMIcon,
-      options: <NativeEmbeddingOptions settings={settings} />,
-      description:
-        "Use the built-in embedding engine for AnythingLLM. Zero setup!",
-    },
-    {
-      name: "OpenAI",
-      value: "openai",
-      logo: OpenAiLogo,
-      options: <OpenAiOptions settings={settings} />,
-      description: "The standard option for most non-commercial use.",
-    },
-    {
-      name: "Azure OpenAI",
-      value: "azure",
-      logo: AzureOpenAiLogo,
-      options: <AzureAiOptions settings={settings} />,
-      description: "The enterprise option of OpenAI hosted on Azure services.",
-    },
-    {
-      name: "Local AI",
-      value: "localai",
-      logo: LocalAiLogo,
-      options: <LocalAiOptions settings={settings} />,
-      description: "Run embedding models locally on your own machine.",
-    },
-    {
-      name: "Ollama",
-      value: "ollama",
-      logo: OllamaLogo,
-      options: <OllamaEmbeddingOptions settings={settings} />,
-      description: "Run embedding models locally on your own machine.",
-    },
-  ];
-
   useEffect(() => {
     const filtered = EMBEDDERS.filter((embedder) =>
       embedder.name.toLowerCase().includes(searchQuery.toLowerCase())
@@ -282,7 +296,7 @@ export default function GeneralEmbeddingPreference() {
                 {selectedEmbedder &&
                   EMBEDDERS.find(
                     (embedder) => embedder.value === selectedEmbedder
-                  )?.options}
+                  )?.options(settings)}
               </div>
             </div>
           </form>
@@ -290,7 +304,7 @@ export default function GeneralEmbeddingPreference() {
       )}
       <ModalWrapper isOpen={isOpen}>
         <ChangeWarningModal
-          warningText="Switching the vector database will ignore previously embedded documents and future similarity search results. They will need to be re-added to each workspace."
+          warningText="Switching the embedding model will break previously embedded documents from working during chat. They will need to un-embed from every workspace and fully removed and re-uploaded so they can be embed by the new embedding model."
           onClose={closeModal}
           onConfirm={handleSaveSettings}
         />
diff --git a/server/models/systemSettings.js b/server/models/systemSettings.js
index a6a7e50f0..20c161cd5 100644
--- a/server/models/systemSettings.js
+++ b/server/models/systemSettings.js
@@ -87,6 +87,7 @@ const SystemSettings = {
     },
   },
   currentSettings: async function () {
+    const { hasVectorCachedFiles } = require("../utils/files");
     const llmProvider = process.env.LLM_PROVIDER;
     const vectorDB = process.env.VECTOR_DB;
     return {
@@ -104,7 +105,8 @@ const SystemSettings = {
       // Embedder Provider Selection Settings & Configs
       // --------------------------------------------------------
       EmbeddingEngine: process.env.EMBEDDING_ENGINE,
-      HasExistingEmbeddings: await this.hasEmbeddings(),
+      HasExistingEmbeddings: await this.hasEmbeddings(), // check if they have any currently embedded documents active in workspaces.
+      HasCachedEmbeddings: hasVectorCachedFiles(), // check if they any currently cached embedded docs.
       EmbeddingBasePath: process.env.EMBEDDING_BASE_PATH,
       EmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
       EmbeddingModelMaxChunkLength:
diff --git a/server/utils/files/index.js b/server/utils/files/index.js
index 83dd229cc..fea6f7f7e 100644
--- a/server/utils/files/index.js
+++ b/server/utils/files/index.js
@@ -192,6 +192,19 @@ function normalizePath(filepath = "") {
   return result;
 }
 
+// Check if the vector-cache folder is empty or not
+// useful for it the user is changing embedders as this will
+// break the previous cache.
+function hasVectorCachedFiles() {
+  try {
+    return (
+      fs.readdirSync(vectorCachePath)?.filter((name) => name.endsWith(".json"))
+        .length !== 0
+    );
+  } catch {}
+  return false;
+}
+
 module.exports = {
   findDocumentInDocuments,
   cachedVectorInformation,
@@ -203,4 +216,5 @@ module.exports = {
   normalizePath,
   isWithin,
   documentsPath,
+  hasVectorCachedFiles,
 };