diff --git a/mlx_vlm/models/pixtral/pixtral.py b/mlx_vlm/models/pixtral/pixtral.py
index 032b43f2..1257d531 100644
--- a/mlx_vlm/models/pixtral/pixtral.py
+++ b/mlx_vlm/models/pixtral/pixtral.py
@@ -75,6 +75,9 @@ def get_input_embeddings(
         # Get the input embeddings from the language model
         inputs_embeds = self.language_model.model.embed_tokens(input_ids)
 
+        # Get number of images
+        num_images = len(pixel_values[0])
+
         # Get the ouptut hidden states from the vision model
         if isinstance(pixel_values, list):
             if input_ids.shape[0] == 1:  # Batch size is 1
@@ -88,8 +91,13 @@ def get_input_embeddings(
         if pixel_values.ndim == 3:
             pixel_values = pixel_values[None, ...]
 
+        pixel_values = mx.split(pixel_values, num_images, axis=2)
+
+        # pass pixel_values as list of images, as each image is individually run through conv2d and position encoding
+        #  reference code from transformers: https://github.com/huggingface/transformers/blob/main/src/transformers/models/pixtral/modeling_pixtral.py#L479C9-L479C21
+        #  and mistral_inference: https://github.com/mistralai/mistral-inference/blob/main/src/mistral_inference/vision_encoder.py#L85
         *_, hidden_states = self.vision_tower(
-            pixel_values.transpose(0, 2, 3, 1), output_hidden_states=True
+            [pv.transpose(0, 2, 3, 1) for pv in pixel_values], output_hidden_states=True
         )
         # Select the hidden states from the desired layer
         selected_image_feature = hidden_states[self.vision_feature_layer]
@@ -119,7 +127,10 @@ def _merge_input_ids_with_image_features(
             text_segments.append(inputs_embeds[:, start_idx:position])
             start_idx = position + 1
 
-        image_embeddings = mx.split(image_features, image_features.shape[0])
+        # [IMG_BREAK] and [IMG_END] are missing with existing implementation
+        # image_embeddings = mx.split(image_features, image_features.shape[0])
+
+        image_embeddings = mx.split(image_features, num_image_patches, axis=1)
         final_embeddings = [v for p in zip(text_segments, image_embeddings) for v in p]
         final_embeddings += [inputs_embeds[:, start_idx:]]
 
diff --git a/mlx_vlm/models/pixtral/vision.py b/mlx_vlm/models/pixtral/vision.py
index 2db77f4d..ce5bce8c 100644
--- a/mlx_vlm/models/pixtral/vision.py
+++ b/mlx_vlm/models/pixtral/vision.py
@@ -1,6 +1,6 @@
 import inspect
 from dataclasses import dataclass
-from typing import Optional
+from typing import Optional, List
 
 import mlx.core as mx
 import mlx.nn as nn
@@ -253,11 +253,11 @@ def __init__(self, config: VisionConfig):
 
     def __call__(
         self,
-        x: mx.array,
+        x: List[mx.array],
         output_hidden_states: Optional[bool] = None,
     ) -> mx.array:
-        B, H, W, C = x.shape
-        patch_embeds_list = [self.patch_conv(img[None, :]) for img in x]
+        B, H, W, C = x[0].shape
+        patch_embeds_list = [self.patch_conv(img) for img in x]
 
         patch_embeds = mx.concatenate(
             [p.reshape(B, -1, p.shape[-1]) for p in patch_embeds_list], axis=1
@@ -299,7 +299,7 @@ def __init__(self, config: VisionConfig):
         self.vision_model = PixtralVisionModel(config)
 
     def __call__(
-        self, x: mx.array, output_hidden_states: Optional[bool] = None
+        self, x: List[mx.array], output_hidden_states: Optional[bool] = None
     ) -> mx.array:
         return self.vision_model(x, output_hidden_states)