diff --git a/gpt4all-bindings/python/gpt4all/gpt4all.py b/gpt4all-bindings/python/gpt4all/gpt4all.py
index 2b901251..5787d293 100644
--- a/gpt4all-bindings/python/gpt4all/gpt4all.py
+++ b/gpt4all-bindings/python/gpt4all/gpt4all.py
@@ -29,7 +29,7 @@ class GPT4All():
             model_name: Name of GPT4All or custom model. Including ".bin" file extension is optional but encouraged.
             model_path: Path to directory containing model file or, if file does not exist, where to download model.
                 Default is None, in which case models will be stored in `~/.cache/gpt4all/`.
-            model_type: Model architecture to use - currently, only options are 'llama' or 'gptj'. Only required if model
+            model_type: Model architecture to use - currently, options are 'llama', 'gptj', or 'mpt'. Only required if model
                 is custom. Note that these models still must be built from llama.cpp or GPTJ ggml architecture.
                 Default is None.
             allow_download: Allow API to download models from gpt4all.io. Default is True. 
@@ -263,6 +263,8 @@ class GPT4All():
             return pyllmodel.GPTJModel()
         elif model_type == "llama":
             return pyllmodel.LlamaModel()
+        elif model_type == "mpt":
+            return pyllmodel.MPTModel()
         else:
             raise ValueError(f"No corresponding model for model_type: {model_type}")
         
@@ -286,13 +288,20 @@ class GPT4All():
             "ggml-vicuna-7b-1.1-q4_2.bin",
             "ggml-vicuna-13b-1.1-q4_2.bin",
             "ggml-wizardLM-7B.q4_2.bin",
-            "ggml-stable-vicuna-13B.q4_2.bin"
+            "ggml-stable-vicuna-13B.q4_2.bin",
+            "ggml-nous-gpt4-vicuna-13b.bin"
+        ]
+
+        MPT_MODELS = [
+            "ggml-mpt-7b-base.bin"
         ]
 
         if model_name in GPTJ_MODELS:
             return pyllmodel.GPTJModel()
         elif model_name in LLAMA_MODELS:
             return pyllmodel.LlamaModel()
+        elif model_name in MPT_MODELS:
+            return pyllmodel.MPTModel()
         else:
             err_msg = f"""No corresponding model for provided filename {model_name}.
             If this is a custom model, make sure to specify a valid model_type.
diff --git a/gpt4all-bindings/python/gpt4all/pyllmodel.py b/gpt4all-bindings/python/gpt4all/pyllmodel.py
index 49ba184e..d194c234 100644
--- a/gpt4all-bindings/python/gpt4all/pyllmodel.py
+++ b/gpt4all-bindings/python/gpt4all/pyllmodel.py
@@ -46,6 +46,9 @@ llmodel.llmodel_gptj_create.restype = ctypes.c_void_p
 llmodel.llmodel_gptj_destroy.argtypes = [ctypes.c_void_p]
 llmodel.llmodel_llama_create.restype = ctypes.c_void_p
 llmodel.llmodel_llama_destroy.argtypes = [ctypes.c_void_p]
+llmodel.llmodel_mpt_create.restype = ctypes.c_void_p
+llmodel.llmodel_mpt_destroy.argtypes = [ctypes.c_void_p]
+
 
 llmodel.llmodel_loadModel.argtypes = [ctypes.c_void_p, ctypes.c_char_p]
 llmodel.llmodel_loadModel.restype = ctypes.c_bool
@@ -236,3 +239,17 @@ class LlamaModel(LLModel):
         if self.model is not None:
             llmodel.llmodel_llama_destroy(self.model)
         super().__del__()
+
+
+class MPTModel(LLModel):
+
+    model_type = "mpt"
+
+    def __init__(self):
+        super().__init__()
+        self.model = llmodel.llmodel_mpt_create()
+
+    def __del__(self):
+        if self.model is not None:
+            llmodel.llmodel_mpt_destroy(self.model)
+        super().__del__()
diff --git a/gpt4all-bindings/python/tests/__init__.py b/gpt4all-bindings/python/tests/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/gpt4all-bindings/python/tests/test_pyllmodel.py b/gpt4all-bindings/python/tests/test_pyllmodel.py
index 5535cb7b..e446b0b5 100644
--- a/gpt4all-bindings/python/tests/test_pyllmodel.py
+++ b/gpt4all-bindings/python/tests/test_pyllmodel.py
@@ -14,6 +14,24 @@ def test_create_llama():
     llama = pyllmodel.LlamaModel()
     assert llama.model_type == "llama"
 
+def test_create_mpt():
+    mpt = pyllmodel.MPTModel()
+    assert mpt.model_type == "mpt"
+
+def prompt_unloaded_mpt():
+    mpt = pyllmodel.MPTModel()
+    old_stdout = sys.stdout 
+    collect_response = StringIO()
+    sys.stdout = collect_response
+
+    mpt.prompt("hello there")
+
+    response = collect_response.getvalue()
+    sys.stdout = old_stdout
+
+    response = response.strip()
+    assert response == "MPT ERROR: prompt won't work with an unloaded model!"
+
 def prompt_unloaded_gptj():
     gptj = pyllmodel.GPTJModel()
     old_stdout = sys.stdout