diff --git a/concrete/common/mlir/utils.py b/concrete/common/mlir/utils.py
index b1242ab2c..e2c588554 100644
--- a/concrete/common/mlir/utils.py
+++ b/concrete/common/mlir/utils.py
@@ -102,8 +102,6 @@ def check_node_compatibility_with_mlir(
 
     elif isinstance(node, intermediate.MatMul):  # constraints for matrix multiplication
         assert_true(len(inputs) == 2)
-        if not value_is_unsigned_integer(inputs[0]) or not value_is_unsigned_integer(inputs[1]):
-            return "only unsigned integer matrix multiplication is supported"
 
     else:  # pragma: no cover
         assert_not_reached("Non IntermediateNode object in the OPGraph")
diff --git a/tests/numpy/test_compile.py b/tests/numpy/test_compile.py
index b80fdc71f..ed23f208e 100644
--- a/tests/numpy/test_compile.py
+++ b/tests/numpy/test_compile.py
@@ -14,6 +14,7 @@ from concrete.common.extensions.table import LookupTable
 from concrete.common.values import ClearTensor, EncryptedScalar, EncryptedTensor
 from concrete.numpy import tracing
 from concrete.numpy.compile import (
+    FHECircuit,
     compile_numpy_function,
     compile_numpy_function_into_op_graph_and_measure_bounds,
 )
@@ -1353,6 +1354,11 @@ def test_compile_and_run_constant_dot_correctness(
             (5, 5),
             (0, 4),
         ),
+        pytest.param(
+            (3, 2),
+            (2, 3),
+            (-4, 3),
+        ),
     ],
 )
 def test_compile_and_run_matmul_correctness(
@@ -1362,10 +1368,16 @@ def test_compile_and_run_matmul_correctness(
 
     low, high = input_range
 
+    check_mod = low < 0 or high < 0
+
+    max_abs = max(abs(low), abs(high))
+
+    # Inputset for x as lhs of matmul
     lhs_inputset = [
         numpy.zeros(lhs_shape, dtype=numpy.uint32),
         numpy.ones(lhs_shape, dtype=numpy.uint32) * high,
     ]
+    # Inputset for x as rhs of matmul
     rhs_inputset = [
         numpy.zeros(rhs_shape, dtype=numpy.uint32),
         numpy.ones(rhs_shape, dtype=numpy.uint32) * high,
@@ -1377,6 +1389,32 @@ def test_compile_and_run_matmul_correctness(
     left_constant = numpy.random.randint(low, high + 1, size=lhs_shape)
     right_constant = numpy.random.randint(low, high + 1, size=rhs_shape)
 
+    # Generate worst case inputsets for bit widths, replacing negative values by 0 and putting
+    # the max value elsewhere, and then doing the same for positive values
+    rhs_inputset.extend(
+        [
+            numpy.where(right_constant < 0, 0, max_abs),
+            numpy.where(right_constant > 0, 0, max_abs),
+        ]
+    )
+    lhs_inputset.extend(
+        [
+            numpy.where(left_constant < 0, 0, max_abs),
+            numpy.where(left_constant > 0, 0, max_abs),
+        ]
+    )
+
+    # Keep inputset positive
+    rhs_inputset = [numpy.clip(val, 0, high) for val in rhs_inputset]
+    lhs_inputset = [numpy.clip(val, 0, high) for val in lhs_inputset]
+
+    def get_output_mod(circuit: FHECircuit):
+        assert len(circuit.op_graph.output_nodes) == 1
+        assert isinstance(
+            output_dtype := circuit.op_graph.get_ordered_outputs()[0].outputs[0].dtype, Integer
+        )
+        return 2 ** output_dtype.bit_width
+
     def using_operator_left(x):
         return x @ right_constant
 
@@ -1414,13 +1452,28 @@ def test_compile_and_run_matmul_correctness(
         default_compilation_configuration,
     )
 
-    lhs_arg = numpy.random.randint(low, high + 1, size=lhs_shape, dtype=numpy.uint8)
-    check_array_equality(operator_left_circuit.run(lhs_arg), using_operator_left(lhs_arg))
-    check_array_equality(function_left_circuit.run(lhs_arg), using_function_left(lhs_arg))
+    def check_result(circuit: FHECircuit, func, arg):
+        # Stay positive for input to FHE circuit
+        arg = numpy.clip(arg, 0, high).astype(numpy.uint8)
 
-    rhs_arg = numpy.random.randint(low, high + 1, size=rhs_shape, dtype=numpy.uint8)
-    check_array_equality(operator_right_circuit.run(rhs_arg), using_operator_right(rhs_arg))
-    check_array_equality(function_right_circuit.run(rhs_arg), using_function_right(rhs_arg))
+        circuit_output = circuit.run(arg)
+        func_output = func(arg)
+
+        if check_mod:
+            output_mod = get_output_mod(circuit)
+
+            circuit_output %= output_mod
+            func_output %= output_mod
+
+        check_array_equality(circuit_output, func_output)
+
+    arg = numpy.random.randint(low, high + 1, size=lhs_shape)
+    check_result(operator_left_circuit, using_operator_left, arg)
+    check_result(function_left_circuit, using_function_left, arg)
+
+    arg = numpy.random.randint(low, high + 1, size=rhs_shape)
+    check_result(operator_right_circuit, using_operator_right, arg)
+    check_result(function_right_circuit, using_function_right, arg)
 
 
 @pytest.mark.parametrize(
@@ -1643,24 +1696,6 @@ return %9
                 """.strip()  # noqa: E501
             ),
         ),
-        pytest.param(
-            lambda x: x @ -numpy.ones(shape=(2, 3), dtype=numpy.int32),
-            {"x": EncryptedTensor(UnsignedInteger(3), shape=(3, 2))},
-            [numpy.random.randint(0, 2 ** 3, size=(3, 2)) for i in range(10)],
-            (
-                """
-
-function you are trying to compile isn't supported for MLIR lowering
-
-%0 = x                              # EncryptedTensor<uint3, shape=(3, 2)>
-%1 = [[-1 -1 -1] [-1 -1 -1]]        # ClearTensor<int2, shape=(2, 3)>
-%2 = matmul(%0, %1)                 # EncryptedTensor<int5, shape=(3, 3)>
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ only unsigned integer matrix multiplication is supported
-return %2
-
-                """.strip()  # noqa: E501
-            ),
-        ),
         pytest.param(
             lambda x: numpy.transpose(x),
             {"x": EncryptedTensor(Integer(3, is_signed=False), shape=(3, 2))},