diff --git a/examples/llm_qat/ARGUMENTS.md b/examples/llm_qat/ARGUMENTS.md
index 579e235c346..0a3e2b7a12d 100644
--- a/examples/llm_qat/ARGUMENTS.md
+++ b/examples/llm_qat/ARGUMENTS.md
@@ -50,7 +50,7 @@
 | Argument | Type | Default | Description |
 |----------|------|---------|-------------|
 | `--recipe` | `str` | `None` | Path to a quantization recipe YAML file (built-in or custom). Built-in recipes can be specified by relative path, e.g. 'general/ptq/nvfp4_default-kv_fp8'. Replaces the deprecated --quant_cfg flag. |
-| `--quant_cfg` | `modelopt.torch.quantization.config.QuantizeConfig` | `None` | Deprecated: pre-quantize the model with a separate quantization step instead. Specify the quantization format for PTQ/QAT by name (e.g. NVFP4_DEFAULT_CFG). |
+| `--quant_cfg` | `str` | `None` | Deprecated: pre-quantize the model with a separate quantization step instead. Specify the quantization format for PTQ/QAT by name (e.g. NVFP4_DEFAULT_CFG). |
 | `--calib_size` | `int` | `512` | Specify the calibration size for quantization. The calibration dataset is used to setup the quantization scale parameters for PTQ/QAT. |
 | `--compress` | `bool` | `False` | Whether to compress the model weights after quantization for QLoRA. This is useful for reducing the model size. |
 | `--calib_batch_size` | `int` | `1` | Batch size for calibration data during quantization. |
diff --git a/modelopt/torch/quantization/plugins/transformers_trainer.py b/modelopt/torch/quantization/plugins/transformers_trainer.py
index 57db3e73b6f..981f3d990d4 100644
--- a/modelopt/torch/quantization/plugins/transformers_trainer.py
+++ b/modelopt/torch/quantization/plugins/transformers_trainer.py
@@ -32,7 +32,6 @@
 from modelopt.torch.opt.plugins.transformers import ModelOptHFArguments
 from modelopt.torch.utils import get_module_device, print_rank_0
 
-from ..config import QuantizeConfig
 from ..nn import TensorQuantizer
 from ..utils import (
     calibrate_with_adapters,
@@ -58,7 +57,7 @@ class QuantizationArguments(ModelOptHFArguments):
             ),
         },
     )
-    quant_cfg: str | QuantizeConfig | None = field(
+    quant_cfg: str | None = field(
         default=None,
         metadata={
             "help": (