diff --git a/src/axolotl/integrations/liger/README.md b/src/axolotl/integrations/liger/README.md
index c5cce8282b..3a2d4bd04b 100644
--- a/src/axolotl/integrations/liger/README.md
+++ b/src/axolotl/integrations/liger/README.md
@@ -18,6 +18,9 @@ liger_rms_norm: true
 liger_glu_activation: true
 liger_layer_norm: true
 liger_fused_linear_cross_entropy: true
+
+# FLCE-specific
+liger_use_token_scaling: true
 ```
 
 ## Supported Models
diff --git a/src/axolotl/integrations/liger/args.py b/src/axolotl/integrations/liger/args.py
index d5bb10cfdd..eb7a6c59be 100644
--- a/src/axolotl/integrations/liger/args.py
+++ b/src/axolotl/integrations/liger/args.py
@@ -16,7 +16,7 @@
 Module for handling LIGER input arguments.
 """
 
-from pydantic import BaseModel, model_validator
+from pydantic import BaseModel, Field, model_validator
 
 from axolotl.utils.logging import get_logger
 
@@ -35,6 +35,15 @@ class LigerArgs(BaseModel):
     liger_glu_activation: bool | None = None
     liger_cross_entropy: bool | None = None
     liger_fused_linear_cross_entropy: bool | None = None
+    liger_use_token_scaling: bool | None = Field(
+        default=None,
+        json_schema_extra={
+            "description": (
+                "Enables use_token_scaling in fused_linear_cross_entropy. "
+                "When True, each token's loss is multiplied by its predicted probability (detached from gradients)."
+            )
+        },
+    )
 
     @model_validator(mode="before")
     @classmethod
@@ -75,6 +84,18 @@ def check_liger_rms_norm_tensor_parallel(cls, data):
             )
         return data
 
+    @model_validator(mode="before")
+    @classmethod
+    def check_liger_use_token_scaling_flce(cls, data):
+        if data.get("liger_use_token_scaling") and not data.get(
+            "liger_fused_linear_cross_entropy"
+        ):
+            raise ValueError(
+                "`liger_use_token_scaling: true` requires `liger_fused_linear_cross_entropy` enabled."
+            )
+
+        return data
+
     @model_validator(mode="after")
     def check_tensor_parallel_size_liger_fused_linear_cross_entropy(self):
         # TODO @SalmanMohammadi this is a larger fix - investigate
diff --git a/src/axolotl/integrations/liger/plugin.py b/src/axolotl/integrations/liger/plugin.py
index 89f7c37b71..ac796c2c90 100644
--- a/src/axolotl/integrations/liger/plugin.py
+++ b/src/axolotl/integrations/liger/plugin.py
@@ -48,6 +48,33 @@ def pre_model_load(self, cfg):
                 "Cannot have both `liger_cross_entropy` and `liger_fused_linear_cross_entropy` set."
             )
 
+        if cfg.liger_use_token_scaling:
+            # Patch FLCE to set token_scaling=True for function and class API
+            from liger_kernel.transformers import functional
+            from liger_kernel.transformers.fused_linear_cross_entropy import (
+                LigerFusedLinearCrossEntropyLoss,
+            )
+
+            old_liger_fused_linear_cross_entropy = (
+                functional.liger_fused_linear_cross_entropy
+            )
+
+            def patched_liger_fused_linear_cross_entropy(*args, **kwargs):
+                kwargs["use_token_scaling"] = True
+                return old_liger_fused_linear_cross_entropy(*args, **kwargs)
+
+            functional.liger_fused_linear_cross_entropy = (
+                patched_liger_fused_linear_cross_entropy
+            )
+
+            old_init = LigerFusedLinearCrossEntropyLoss.__init__
+
+            def patched_init(self, *args, **kwargs):
+                kwargs["use_token_scaling"] = True
+                return old_init(self, *args, **kwargs)
+
+            LigerFusedLinearCrossEntropyLoss.__init__ = patched_init
+
         if cfg.model_config_type in MODEL_TYPE_TO_APPLY_LIGER_FN:
             apply_liger_fn = MODEL_TYPE_TO_APPLY_LIGER_FN[cfg.model_config_type]
             liger_fn_sig = inspect.signature(apply_liger_fn)
diff --git a/tests/e2e/integrations/test_liger.py b/tests/e2e/integrations/test_liger.py
index 2859699633..55317151e5 100644
--- a/tests/e2e/integrations/test_liger.py
+++ b/tests/e2e/integrations/test_liger.py
@@ -2,6 +2,7 @@
 Simple end-to-end test for Liger integration
 """
 
+import pytest
 from axolotl.common.datasets import load_datasets
 from axolotl.train import train
 from axolotl.utils.config import normalize_config, prepare_plugins, validate_config
@@ -62,7 +63,11 @@ def test_llama_wo_flce(self, temp_dir):
         check_model_output_exists(temp_dir, cfg)
 
     @require_torch_2_4_1
-    def test_llama_w_flce(self, temp_dir):
+    @pytest.mark.parametrize(
+        "liger_use_token_scaling",
+        [True, False],
+    )
+    def test_llama_w_flce(self, temp_dir, liger_use_token_scaling):
         cfg = DictDefault(
             {
                 "base_model": "HuggingFaceTB/SmolLM2-135M",
@@ -74,6 +79,7 @@ def test_llama_w_flce(self, temp_dir):
                 "liger_glu_activation": True,
                 "liger_cross_entropy": False,
                 "liger_fused_linear_cross_entropy": True,
+                "liger_use_token_scaling": liger_use_token_scaling,
                 "sequence_len": 1024,
                 "val_set_size": 0.05,
                 "special_tokens": {
diff --git a/tests/integrations/test_liger.py b/tests/integrations/test_liger.py
index d7b171ec27..6865306c9d 100644
--- a/tests/integrations/test_liger.py
+++ b/tests/integrations/test_liger.py
@@ -75,3 +75,19 @@ def test_conflict_swiglu_ligergluactivation(self, minimal_liger_cfg):
         ):
             prepare_plugins(test_cfg)
             validate_config(test_cfg)
+
+    def test_use_token_scaling_require_flce(self, minimal_liger_cfg):
+        test_cfg = DictDefault(
+            {
+                "liger_fused_linear_cross_entropy": False,
+                "liger_use_token_scaling": True,
+            }
+            | minimal_liger_cfg
+        )
+
+        with pytest.raises(
+            ValueError,
+            match=r"`liger_use_token_scaling: true` requires `liger_fused_linear_cross_entropy` enabled.",
+        ):
+            prepare_plugins(test_cfg)
+            validate_config(test_cfg)