diff --git a/src/compressed_tensors/compressors/model_compressor.py b/src/compressed_tensors/compressors/model_compressor.py
index b8bf0001..9807cbec 100644
--- a/src/compressed_tensors/compressors/model_compressor.py
+++ b/src/compressed_tensors/compressors/model_compressor.py
@@ -240,6 +240,56 @@ def compress(
                 compressed_state_dict
             )
 
+        # HACK (mgoin): Post-process step for kv cache scales to take the
+        # k/v_proj module `output_scale` parameters, and store them in the
+        # parent attention module as `k_scale` and `v_scale`
+        #
+        # Example:
+        #  Replace `model.layers.0.self_attn.k_proj.output_scale`
+        #  with    `model.layers.0.self_attn.k_scale`
+        if self.quantization_config.kv_cache_scheme is not None:
+            # HACK (mgoin): We assume the quantized modules in question
+            # will be k_proj and v_proj since those are the default targets.
+            # We check that both of these modules have output activation
+            # quantization, and additionally check that q_proj doesn't.
+            q_proj_has_no_quant_output = 0
+            k_proj_has_quant_output = 0
+            v_proj_has_quant_output = 0
+            for name, module in model.named_modules():
+                if not hasattr(module, "quantization_scheme"):
+                    continue
+                out_act = module.quantization_scheme.output_activations
+                if name.endswith(".q_proj") and out_act is None:
+                    q_proj_has_no_quant_output += 1
+                elif name.endswith(".k_proj") and out_act is not None:
+                    k_proj_has_quant_output += 1
+                elif name.endswith(".v_proj") and out_act is not None:
+                    v_proj_has_quant_output += 1
+
+            assert (
+                q_proj_has_no_quant_output > 0
+                and k_proj_has_quant_output > 0
+                and v_proj_has_quant_output > 0
+            )
+            assert (
+                q_proj_has_no_quant_output
+                == k_proj_has_quant_output
+                == v_proj_has_quant_output
+            )
+
+            # Move all .k/v_proj.output_scale parameters to .k/v_scale
+            working_state_dict = {}
+            for key in compressed_state_dict.keys():
+                if key.endswith(".k_proj.output_scale"):
+                    new_key = key.replace(".k_proj.output_scale", ".k_scale")
+                    working_state_dict[new_key] = compressed_state_dict[key]
+                elif key.endswith(".v_proj.output_scale"):
+                    new_key = key.replace(".v_proj.output_scale", ".v_scale")
+                    working_state_dict[new_key] = compressed_state_dict[key]
+                else:
+                    working_state_dict[key] = compressed_state_dict[key]
+            compressed_state_dict = working_state_dict
+
         # HACK: Override the dtype_byte_size function in transformers to
         # support float8 types. Fix is posted upstream
         # https://github.com/huggingface/transformers/pull/30488