diff --git a/milli/src/vector/openai.rs b/milli/src/vector/openai.rs
index 20013d8e8..8712c7894 100644
--- a/milli/src/vector/openai.rs
+++ b/milli/src/vector/openai.rs
@@ -65,14 +65,10 @@ impl EmbeddingModel {
         }
     }
 
-    pub fn dimensions(&self) -> usize {
+    pub fn default_dimensions(&self) -> usize {
         match self {
             EmbeddingModel::TextEmbeddingAda002 => 1536,
-
-            //Default value for the model
             EmbeddingModel::TextEmbedding3Large => 1536,
-
-            //Default value for the model
             EmbeddingModel::TextEmbedding3Small => 3072,
         }
     }
@@ -108,7 +104,7 @@ impl EmbeddingModel {
         }
     }
 
-    pub fn is_optional_dimensions_supported(&self) -> bool {
+    pub fn supports_overriding_dimensions(&self) -> bool {
         match self {
             EmbeddingModel::TextEmbeddingAda002 => false,
             EmbeddingModel::TextEmbedding3Large => true,
@@ -275,7 +271,7 @@ impl Embedder {
         let request = OpenAiRequest {
             model: self.options.embedding_model.name(),
             input: texts,
-            dimension: if self.options.embedding_model.is_optional_dimensions_supported() {
+            dimension: if self.options.embedding_model.supports_overriding_dimensions() {
                 self.options.dimensions.as_ref()
             } else {
                 None
@@ -323,8 +319,7 @@ impl Embedder {
             }
 
             let mut tokens = encoded.as_slice();
-            let mut embeddings_for_prompt =
-                Embeddings::new(self.options.embedding_model.dimensions());
+            let mut embeddings_for_prompt = Embeddings::new(self.dimensions());
             while tokens.len() > max_token_count {
                 let window = &tokens[..max_token_count];
                 embeddings_for_prompt.push(self.embed_tokens(window, client).await?).unwrap();
@@ -409,7 +404,11 @@ impl Embedder {
     }
 
     pub fn dimensions(&self) -> usize {
-        self.options.dimensions.unwrap_or_else(|| self.options.embedding_model.dimensions())
+        if self.options.embedding_model.supports_overriding_dimensions() {
+            self.options.dimensions.unwrap_or(self.options.embedding_model.default_dimensions())
+        } else {
+            self.options.embedding_model.default_dimensions()
+        }
     }
 
     pub fn distribution(&self) -> Option<DistributionShift> {