diff --git a/tests/max-pool-model.onnx b/tests/max-pool-model.onnx
new file mode 100644
index 0000000000000000000000000000000000000000..e3b60d9793f1540ad9e5f829a132e73141b1cc09
--- /dev/null
+++ b/tests/max-pool-model.onnx
@@ -0,0 +1,21 @@
+finn-hls-onnx-model:ø

+p
+inout"StreamingMaxPool*
+ImgDim 
*
+NumChannels 
*
+PoolDim 
*
+backend"fpgadataflow 
:finnmax_pool_graphZ
+in
+

+
+
+b
+out
+

+
+
+r
+in
+
finn_datatypeBIPOLARr
+out
+
finn_datatypeBIPOLARB
\ No newline at end of file
diff --git a/tests/test_layer_streaming_maxpool.py b/tests/test_layer_streaming_maxpool.py
new file mode 100644
index 0000000000000000000000000000000000000000..70557ca7802d57fbf2f6dd5e1ce013dee979800c
--- /dev/null
+++ b/tests/test_layer_streaming_maxpool.py
@@ -0,0 +1,35 @@
+# import onnx
+from onnx import TensorProto, helper
+
+from finn.core.datatype import DataType
+from finn.core.modelwrapper import ModelWrapper
+
+
+def test_layer_streaming_maxpool():
+    inp = helper.make_tensor_value_info("in", TensorProto.FLOAT, [2, 4, 4])
+    outp = helper.make_tensor_value_info("out", TensorProto.FLOAT, [2, 2, 2])
+
+    MaxPool_node = helper.make_node(
+        "StreamingMaxPool",
+        ["in"],
+        ["out"],
+        domain="finn",
+        backend="fpgadataflow",
+        ImgDim=4,
+        PoolDim=2,
+        NumChannels=2,
+    )
+
+    graph = helper.make_graph(
+        nodes=[MaxPool_node], name="max_pool_graph", inputs=[inp], outputs=[outp],
+    )
+    model = helper.make_model(graph, producer_name="finn-hls-onnx-model")
+    model = ModelWrapper(model)
+
+    # set the tensor datatypes (in this case: all to bipolar)
+    for tensor in graph.input:
+        model.set_tensor_datatype(tensor.name, DataType["BIPOLAR"])
+    for tensor in graph.output:
+        model.set_tensor_datatype(tensor.name, DataType["BIPOLAR"])
+
+    # onnx.save(model.model, "max-pool-model.onnx")