diff --git a/modules/model_quant_nncf.py b/modules/model_quant_nncf.py
index 09a00cdd4..cdcf054f5 100644
--- a/modules/model_quant_nncf.py
+++ b/modules/model_quant_nncf.py
@@ -62,21 +62,26 @@ def nncf_compress_layer(layer, num_bits, is_asym_mode, torch_dtype=None, quant_c
             reduction_axes = [i for i in range(layer.weight.ndim) if i != 1]
         else:
             reduction_axes = -1
-            if shared.opts.nncf_compress_weights_num_of_groups > 1 or num_bits == 4:
-                num_of_groups = shared.opts.nncf_compress_weights_num_of_groups
+            if shared.opts.nncf_compress_weights_group_size > 0 or (num_bits == 4 and shared.opts.nncf_compress_weights_group_size != -1):
+                group_size = shared.opts.nncf_compress_weights_group_size
                 channel_size = layer.weight.shape[-1]
 
-                if num_of_groups > channel_size:
-                    group_size = 1
-                    num_of_groups = channel_size
-                elif num_of_groups == 0:
-                    group_size = 128
+                if group_size == 0:
+                    group_size = 64
                     num_of_groups = channel_size // group_size
+
+                if group_size >= channel_size:
+                    group_size = channel_size
+                    num_of_groups = 1
                 else:
-                    group_size = channel_size / num_of_groups
-                while channel_size % group_size != 0: # find something divisible
-                    num_of_groups -= 1
-                    group_size = channel_size / num_of_groups
+                    num_of_groups = channel_size // group_size
+                    while channel_size % group_size != 0: # find something divisible
+                        num_of_groups -= 1
+                        if num_of_groups <= 1:
+                            group_size = channel_size
+                            num_of_groups = 1
+                            break
+                        group_size = channel_size / num_of_groups
 
                 if num_of_groups > 1:
                     result_shape = layer.weight.shape
diff --git a/modules/shared.py b/modules/shared.py
index ee27a44b9..ca9f10235 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -545,8 +545,7 @@ options_templates.update(options_section(('quantization', "Quantization Settings
     "nncf_compress_mode": OptionInfo("post", "Quantization mode", gr.Dropdown, {"choices": ['pre', 'post'], "visible": native and not cmd_opts.use_openvino}),
     "nncf_compress_weights_mode": OptionInfo("INT8_SYM", "Quantization type", gr.Dropdown, {"choices": ['INT8', 'INT8_SYM', 'INT4_ASYM', 'INT4_SYM', 'NF4'] if cmd_opts.use_openvino else ['INT8', 'INT8_SYM', 'INT4', 'INT4_SYM']}),
     "nncf_compress_weights_raito": OptionInfo(0, "Compress ratio", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01, "visible": cmd_opts.use_openvino}),
-    "nncf_compress_weights_group_size": OptionInfo(0, "Group size", gr.Slider, {"minimum": -1, "maximum": 512, "step": 1, "visible": cmd_opts.use_openvino}),
-    "nncf_compress_weights_num_of_groups": OptionInfo(0, "Number of quantization groups", gr.Slider, {"minimum": 0, "maximum": 128, "step": 1, "visible": native and not cmd_opts.use_openvino}),
+    "nncf_compress_weights_group_size": OptionInfo(0, "Group size", gr.Slider, {"minimum": -1, "maximum": 4096, "step": 1, "visible": native}),
     "nncf_quantize": OptionInfo([], "OpenVINO enabled", gr.CheckboxGroup, {"choices": ["Model", "VAE", "TE"], "visible": cmd_opts.use_openvino}),
     "nncf_quantize_mode": OptionInfo("INT8", "OpenVINO activations mode", gr.Dropdown, {"choices": ['INT8', 'FP8_E4M3', 'FP8_E5M2'], "visible": cmd_opts.use_openvino}),
     "nncf_quantize_conv_layers": OptionInfo(False, "Quantize the convolutional layers", gr.Checkbox, {"visible": native and not cmd_opts.use_openvino}),