diff --git a/model_compression_toolkit/core/common/quantization/node_quantization_config.py b/model_compression_toolkit/core/common/quantization/node_quantization_config.py
index e1df6e4e8..d93eb5acb 100644
--- a/model_compression_toolkit/core/common/quantization/node_quantization_config.py
+++ b/model_compression_toolkit/core/common/quantization/node_quantization_config.py
@@ -98,6 +98,9 @@ def __init__(self, op_cfg: OpQuantizationConfig):
         self.activation_quantization_params = {}
         # TODO: computed by compute_activation_bias_correction. Probably shouldnt be here.
         self.activation_bias_correction_term = None
+        # Z-threshold is a global param from QuantizationConfig, however it can be overridden per node by NetworkEditor.
+        # Since activation qparams are re-computed in several places, it's easier to keep it here and update it once.
+        self.z_threshold = None
 
     @property
     def enable_activation_quantization(self):
diff --git a/model_compression_toolkit/core/common/quantization/quantization_params_generation/qparams_activations_computation.py b/model_compression_toolkit/core/common/quantization/quantization_params_generation/qparams_activations_computation.py
index 94a71f834..3ed8b7b70 100644
--- a/model_compression_toolkit/core/common/quantization/quantization_params_generation/qparams_activations_computation.py
+++ b/model_compression_toolkit/core/common/quantization/quantization_params_generation/qparams_activations_computation.py
@@ -47,9 +47,12 @@ def compute_activation_qparams(quant_cfg: QuantizationConfig,
         node_activation_quant_cfg.activation_quantization_method, no_clipping=node_prior_info.is_output_bounded())
 
     # Extract and filter histogram data from the statistics container.
+    z_threshold = quant_cfg.z_threshold
+    if node_activation_quant_cfg.z_threshold is not None:
+        z_threshold = node_activation_quant_cfg.z_threshold
     bins_values, bins_counts = _get_histogram_data(out_stats_container,
                                                    activation_error_method=quant_cfg.activation_error_method,
-                                                   z_threshold=quant_cfg.z_threshold)
+                                                   z_threshold=z_threshold)
 
     # Retrieve the minimum and maximum values from the statistics container.
     min_value, max_value = out_stats_container.get_min_max_values()
diff --git a/tests_pytest/common_tests/unit_tests/core/quantization/quantization_params_selection/test_qarams_activations_computation.py b/tests_pytest/common_tests/unit_tests/core/quantization/quantization_params_selection/test_qarams_activations_computation.py
index 3accd5e47..4c84cf091 100644
--- a/tests_pytest/common_tests/unit_tests/core/quantization/quantization_params_selection/test_qarams_activations_computation.py
+++ b/tests_pytest/common_tests/unit_tests/core/quantization/quantization_params_selection/test_qarams_activations_computation.py
@@ -55,7 +55,7 @@ def _create_activation_quant_cfg(self, quant_method, n_bits=8, signedness=Signed
         op_cfg = OpQuantizationConfig(
             default_weight_attr_config=AttributeQuantizationConfig(),
             attr_weights_configs_mapping={},
-            activation_quantization_method=QuantizationMethod.POWER_OF_TWO,
+            activation_quantization_method=quant_method,
             activation_n_bits=n_bits,
             supported_input_activation_n_bits=n_bits,
             enable_activation_quantization=True,
@@ -66,7 +66,6 @@ def _create_activation_quant_cfg(self, quant_method, n_bits=8, signedness=Signed
             signedness=signedness
         )
         activation_quant_cfg = NodeActivationQuantizationConfig(op_cfg)
-        activation_quant_cfg.activation_quantization_method = quant_method
         return activation_quant_cfg
 
     def test_get_histogram_data_error_method(self):
@@ -190,3 +189,25 @@ def test_get_activations_qparams(self, quant_method, activation_quantization_par
         activation_quant_cfg = self._create_activation_quant_cfg(quant_method, n_bits=2)
         result = compute_activation_qparams(QuantizationConfig(), activation_quant_cfg, nodes_prior_info, stats)
         assert result == expected_result
+
+    def test_overriden_z_thresh(self, mocker):
+        """ Check that correct z-threshold is passed to _get_histogram_data """
+        spy = mocker.patch('model_compression_toolkit.core.common.quantization.quantization_params_generation.'
+                           'qparams_activations_computation._get_histogram_data',
+                           return_value=(np.array([1, 2]), np.array([100])))
+        stat_collector_mock = mocker.Mock(spec_set=StatsCollector, get_min_max_values=lambda: (-1, 1))
+
+        acfg = self._create_activation_quant_cfg(QuantizationMethod.POWER_OF_TWO)
+        assert acfg.z_threshold is None
+        compute_activation_qparams(QuantizationConfig(z_threshold=100), acfg, NodePriorInfo(), stat_collector_mock)
+        # z-threshold from quant config is used
+        assert spy.called_once_with(stat_collector_mock,
+                                    activation_error_method=QuantizationMethod.POWER_OF_TWO,
+                                    z_threshold=100)
+
+        # z-threshold from the node should be used
+        acfg.z_threshold = 5
+        compute_activation_qparams(QuantizationConfig(z_threshold=100), acfg, NodePriorInfo(), stat_collector_mock)
+        assert spy.called_with(stat_collector_mock,
+                               activation_error_method=QuantizationMethod.POWER_OF_TWO,
+                               z_threshold=5)