diff --git a/docs/examples/Supported_Models.ipynb b/docs/examples/Supported_Models.ipynb
index c180b9ea..8c100d12 100644
--- a/docs/examples/Supported_Models.ipynb
+++ b/docs/examples/Supported_Models.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -110,14 +110,22 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
+       "      <td>sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2</td>\n",
+       "      <td>384</td>\n",
+       "      <td>Sentence Transformer model, paraphrase-multilingual-MiniLM-L12-v2</td>\n",
+       "      <td>0.46</td>\n",
+       "      <td>{'hf': 'qdrant/paraphrase-multilingual-MiniLM-L12-v2-onnx-Q'}</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
        "      <td>nomic-ai/nomic-embed-text-v1</td>\n",
        "      <td>768</td>\n",
        "      <td>8192 context length english model</td>\n",
        "      <td>0.54</td>\n",
-       "      <td>{'hf': 'xenova/nomic-embed-text-v1'}</td>\n",
+       "      <td>{'hf': 'nomic-ai/nomic-embed-text-v1'}</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
+       "      <th>10</th>\n",
        "      <td>intfloat/multilingual-e5-large</td>\n",
        "      <td>1024</td>\n",
        "      <td>Multilingual model, e5-large. Recommend using this model for non-English languages</td>\n",
@@ -125,7 +133,7 @@
        "      <td>{'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-multilingual-e5-large.tar.gz', 'hf': 'qdrant/multilingual-e5-large-onnx'}</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
+       "      <th>11</th>\n",
        "      <td>sentence-transformers/paraphrase-multilingual-mpnet-base-v2</td>\n",
        "      <td>768</td>\n",
        "      <td>Sentence-transformers model for tasks like clustering or semantic search</td>\n",
@@ -133,7 +141,7 @@
        "      <td>{'hf': 'xenova/paraphrase-multilingual-mpnet-base-v2'}</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11</th>\n",
+       "      <th>12</th>\n",
        "      <td>jinaai/jina-embeddings-v2-base-en</td>\n",
        "      <td>768</td>\n",
        "      <td>English embedding model supporting 8192 sequence length</td>\n",
@@ -141,7 +149,7 @@
        "      <td>{'hf': 'xenova/jina-embeddings-v2-base-en'}</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
+       "      <th>13</th>\n",
        "      <td>jinaai/jina-embeddings-v2-small-en</td>\n",
        "      <td>512</td>\n",
        "      <td>English embedding model supporting 8192 sequence length</td>\n",
@@ -162,11 +170,12 @@
        "5                                        BAAI/bge-small-en-v1.5   384   \n",
        "6                                        BAAI/bge-small-zh-v1.5   512   \n",
        "7                        sentence-transformers/all-MiniLM-L6-v2   384   \n",
-       "8                                  nomic-ai/nomic-embed-text-v1   768   \n",
-       "9                                intfloat/multilingual-e5-large  1024   \n",
-       "10  sentence-transformers/paraphrase-multilingual-mpnet-base-v2   768   \n",
-       "11                            jinaai/jina-embeddings-v2-base-en   768   \n",
-       "12                           jinaai/jina-embeddings-v2-small-en   512   \n",
+       "8   sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2   384   \n",
+       "9                                  nomic-ai/nomic-embed-text-v1   768   \n",
+       "10                               intfloat/multilingual-e5-large  1024   \n",
+       "11  sentence-transformers/paraphrase-multilingual-mpnet-base-v2   768   \n",
+       "12                            jinaai/jina-embeddings-v2-base-en   768   \n",
+       "13                           jinaai/jina-embeddings-v2-small-en   512   \n",
        "\n",
        "                                                                           description  \\\n",
        "0                                                                   Base English model   \n",
@@ -177,11 +186,12 @@
        "5                                                       Fast and Default English model   \n",
        "6                                                   Fast and recommended Chinese model   \n",
        "7                                             Sentence Transformer model, MiniLM-L6-v2   \n",
-       "8                                                    8192 context length english model   \n",
-       "9   Multilingual model, e5-large. Recommend using this model for non-English languages   \n",
-       "10            Sentence-transformers model for tasks like clustering or semantic search   \n",
-       "11                             English embedding model supporting 8192 sequence length   \n",
+       "8                    Sentence Transformer model, paraphrase-multilingual-MiniLM-L12-v2   \n",
+       "9                                                    8192 context length english model   \n",
+       "10  Multilingual model, e5-large. Recommend using this model for non-English languages   \n",
+       "11            Sentence-transformers model for tasks like clustering or semantic search   \n",
        "12                             English embedding model supporting 8192 sequence length   \n",
+       "13                             English embedding model supporting 8192 sequence length   \n",
        "\n",
        "    size_in_GB  \\\n",
        "0         0.50   \n",
@@ -192,11 +202,12 @@
        "5         0.13   \n",
        "6         0.10   \n",
        "7         0.09   \n",
-       "8         0.54   \n",
-       "9         2.24   \n",
-       "10        1.11   \n",
-       "11        0.55   \n",
-       "12        0.13   \n",
+       "8         0.46   \n",
+       "9         0.54   \n",
+       "10        2.24   \n",
+       "11        1.11   \n",
+       "12        0.55   \n",
+       "13        0.13   \n",
        "\n",
        "                                                                                                                                           sources  \n",
        "0                                                               {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-bge-base-en.tar.gz'}  \n",
@@ -207,14 +218,15 @@
        "5                {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-bge-small-en-v1.5.tar.gz', 'hf': 'qdrant/bge-small-en-v1.5-onnx-q'}  \n",
        "6                                                         {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-bge-small-zh-v1.5.tar.gz'}  \n",
        "7   {'url': 'https://storage.googleapis.com/qdrant-fastembed/sentence-transformers-all-MiniLM-L6-v2.tar.gz', 'hf': 'qdrant/all-MiniLM-L6-v2-onnx'}  \n",
-       "8                                                                                                             {'hf': 'xenova/nomic-embed-text-v1'}  \n",
-       "9          {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-multilingual-e5-large.tar.gz', 'hf': 'qdrant/multilingual-e5-large-onnx'}  \n",
-       "10                                                                                          {'hf': 'xenova/paraphrase-multilingual-mpnet-base-v2'}  \n",
-       "11                                                                                                     {'hf': 'xenova/jina-embeddings-v2-base-en'}  \n",
-       "12                                                                                                    {'hf': 'xenova/jina-embeddings-v2-small-en'}  "
+       "8                                                                                    {'hf': 'qdrant/paraphrase-multilingual-MiniLM-L12-v2-onnx-Q'}  \n",
+       "9                                                                                                           {'hf': 'nomic-ai/nomic-embed-text-v1'}  \n",
+       "10         {'url': 'https://storage.googleapis.com/qdrant-fastembed/fast-multilingual-e5-large.tar.gz', 'hf': 'qdrant/multilingual-e5-large-onnx'}  \n",
+       "11                                                                                          {'hf': 'xenova/paraphrase-multilingual-mpnet-base-v2'}  \n",
+       "12                                                                                                     {'hf': 'xenova/jina-embeddings-v2-base-en'}  \n",
+       "13                                                                                                    {'hf': 'xenova/jina-embeddings-v2-small-en'}  "
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -244,7 +256,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
+   "version": "3.11.4"
   },
   "orig_nbformat": 4
  },
diff --git a/fastembed/models.json b/fastembed/models.json
index e370c74a..f10bd3af 100644
--- a/fastembed/models.json
+++ b/fastembed/models.json
@@ -110,6 +110,16 @@
             "https://storage.googleapis.com/qdrant-fastembed/sentence-transformers-all-MiniLM-L6-v2.tar.gz"
         ]
     },
+    {
+        "model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
+        "dim": 384,
+        "description": "Sentence Transformer model, paraphrase-multilingual-MiniLM-L12-v2",
+        "size_in_GB": 0.46,
+        "hf_sources": [
+            "qdrant/paraphrase-multilingual-MiniLM-L12-v2-onnx-Q"
+        ],
+        "compressed_url_sources": []
+    },
     {
         "model": "xenova/multilingual-e5-large",
         "dim": 1024,
diff --git a/fastembed/text/onnx_embedding.py b/fastembed/text/onnx_embedding.py
index 165f6eb4..1d194450 100644
--- a/fastembed/text/onnx_embedding.py
+++ b/fastembed/text/onnx_embedding.py
@@ -98,6 +98,15 @@
             "hf": "qdrant/all-MiniLM-L6-v2-onnx",
         },
     },
+    {
+        "model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
+        "dim": 384,
+        "description": "Sentence Transformer model, paraphrase-multilingual-MiniLM-L12-v2",
+        "size_in_GB": 0.46,
+        "sources": {
+            "hf": "qdrant/paraphrase-multilingual-MiniLM-L12-v2-onnx-Q",
+        },
+    },
     {
         "model": "nomic-ai/nomic-embed-text-v1",
         "dim": 768,
diff --git a/tests/test_onnx_embeddings.py b/tests/test_onnx_embeddings.py
index 7f580e6b..ea255af2 100644
--- a/tests/test_onnx_embeddings.py
+++ b/tests/test_onnx_embeddings.py
@@ -13,6 +13,7 @@
     "BAAI/bge-base-en-v1.5": np.array([0.01129394, 0.05493144, 0.02615099, 0.00328772, 0.02996045]),
     "BAAI/bge-large-en-v1.5": np.array([0.03434538, 0.03316108, 0.02191251, -0.03713358, -0.01577825]),
     "sentence-transformers/all-MiniLM-L6-v2": np.array([0.0259, 0.0058, 0.0114, 0.0380, -0.0233]),
+    "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2": np.array([0.0094,  0.0184,  0.0328,  0.0072, -0.0351]),
     "intfloat/multilingual-e5-large": np.array([0.0098, 0.0045, 0.0066, -0.0354, 0.0070]),
     "xenova/multilingual-e5-large": np.array([0.00975464, 0.00446568, 0.00655449, -0.0354155, 0.00702112]),
     "xenova/paraphrase-multilingual-mpnet-base-v2": np.array(
diff --git a/tests/test_text_onnx_embeddings.py b/tests/test_text_onnx_embeddings.py
index 8f523adf..81bcbbd3 100644
--- a/tests/test_text_onnx_embeddings.py
+++ b/tests/test_text_onnx_embeddings.py
@@ -14,6 +14,7 @@
     "BAAI/bge-large-en-v1.5": np.array([0.03434538, 0.03316108, 0.02191251, -0.03713358, -0.01577825]),
     "BAAI/bge-large-en-v1.5-quantized": np.array([0.03434538, 0.03316108, 0.02191251, -0.03713358, -0.01577825]),
     "sentence-transformers/all-MiniLM-L6-v2": np.array([0.0259, 0.0058, 0.0114, 0.0380, -0.0233]),
+    "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2": np.array([0.0094,  0.0184,  0.0328,  0.0072, -0.0351]),
     "intfloat/multilingual-e5-large": np.array([0.0098, 0.0045, 0.0066, -0.0354, 0.0070]),
     "sentence-transformers/paraphrase-multilingual-mpnet-base-v2": np.array(
         [-0.01341097, 0.0416553, -0.00480805, 0.02844842, 0.0505299]