diff --git a/fastembed/text/builtin_sentence_embedding.py b/fastembed/text/builtin_sentence_embedding.py
index 430ea7ca..c553c63e 100644
--- a/fastembed/text/builtin_sentence_embedding.py
+++ b/fastembed/text/builtin_sentence_embedding.py
@@ -8,6 +8,21 @@
 
 
 supported_builtin_sentence_embedding_models: list[DenseModelDescription] = [
+    DenseModelDescription(
+        model="ibm-granite/granite-embedding-small-english-r2",
+        dim=384,
+        description=(
+            "Text embeddings, Unimodal (text), English, 8192 input tokens truncation, "
+            "Granite small english r2 model. 2025 year."
+        ),
+        license="apache-2.0",
+        size_in_GB=0.18,
+        sources=ModelSource(
+            hf="onnx-community/granite-embedding-small-english-r2-ONNX",
+        ),
+        model_file="onnx/model.onnx",
+        additional_files=["onnx/model.onnx_data"],
+    ),
     DenseModelDescription(
         model="google/embeddinggemma-300m",
         dim=768,
diff --git a/tests/test_text_onnx_embeddings.py b/tests/test_text_onnx_embeddings.py
index 8744b617..e0dd2317 100644
--- a/tests/test_text_onnx_embeddings.py
+++ b/tests/test_text_onnx_embeddings.py
@@ -31,6 +31,9 @@
     "BAAI/bge-large-en-v1.5-quantized": np.array(
         [0.03434538, 0.03316108, 0.02191251, -0.03713358, -0.01577825]
     ),
+    "ibm-granite/granite-embedding-small-english-r2": np.array(
+        [0.47021756, -0.08181943, -0.97021246, 0.10116885, -0.16487208]
+    ),
     "sentence-transformers/all-MiniLM-L6-v2": np.array(
         [-0.034478, 0.03102, 0.00673, 0.02611, -0.039362]
     ),