diff --git a/src/llm.js b/src/llm.js
index 0351657..db8d42e 100644
--- a/src/llm.js
+++ b/src/llm.js
@@ -5,7 +5,10 @@
 const LITELLM_URL = process.env.LITELLM_URL ?? 'http://llm:4000';
 const LITELLM_KEY = process.env.LITELLM_API_KEY ?? '';
 const TRANSLATE_MODEL = process.env.TRANSLATE_MODEL ?? 'gemini-2.5-flash';
-const EMBED_MODEL = process.env.TRANSLATE_EMBED_MODEL ?? 'mxbai-embed-large';
+const EMBED_MODEL = process.env.TRANSLATE_EMBED_MODEL ?? 'text-embedding-3-small';
+// SmartTranslate translation_memory.embedding is vector(1024); text-embedding-3-*
+// supports runtime dimension reduction via the `dimensions` parameter.
+const EMBED_DIMENSIONS = parseInt(process.env.TRANSLATE_EMBED_DIMENSIONS ?? '1024');
 
 function headers() {
   const h = { 'Content-Type': 'application/json' };
@@ -17,7 +20,7 @@ export async function embed(text) {
   const r = await fetch(`${LITELLM_URL}/v1/embeddings`, {
     method: 'POST',
     headers: headers(),
-    body: JSON.stringify({ model: EMBED_MODEL, input: text }),
+    body: JSON.stringify({ model: EMBED_MODEL, input: text, dimensions: EMBED_DIMENSIONS }),
   });
   if (!r.ok) throw new Error(`embed ${r.status}: ${await r.text()}`);
   const j = await r.json();