diff --git a/src/axolotl/utils/schemas/validation.py b/src/axolotl/utils/schemas/validation.py
index cb467c8f6..a94270c92 100644
--- a/src/axolotl/utils/schemas/validation.py
+++ b/src/axolotl/utils/schemas/validation.py
@@ -1456,21 +1456,6 @@ class StreamingValidationMixin:
 
         return self
 
-    @model_validator(mode="after")
-    def check_streaming_skip_prepare_dataset(self):
-        """Ensure skip_prepare_dataset is set for streaming datasets."""
-        # Check if streaming is enabled for training datasets
-        if self._is_streaming_enabled():
-            skip_prepare = getattr(self, "skip_prepare_dataset", None)
-            if skip_prepare is False:
-                LOG.warning(
-                    "skip_prepare_dataset=False is not compatible with streaming "
-                    "datasets. Setting skip_prepare_dataset=True."
-                )
-            self.skip_prepare_dataset = True
-
-        return self
-
     @model_validator(mode="after")
     def check_dataset_mixing_weights(self):
         """Validate dataset mixing weights configuration."""
diff --git a/tests/e2e/test_streaming.py b/tests/e2e/test_streaming.py
index c10952c6b..1425fc859 100644
--- a/tests/e2e/test_streaming.py
+++ b/tests/e2e/test_streaming.py
@@ -85,84 +85,6 @@ class TestStreamingDatasets:
             "Train Loss (%s) is too high",
         )
 
-    def test_streaming_eval_specific_mixing(self, temp_dir):
-        """Test eval-specific mixing strategy override"""
-
-        cfg = DictDefault(
-            {
-                "base_model": "HuggingFaceTB/SmolLM2-135M",
-                "flash_attention": True,
-                "sequence_len": 512,
-                "sample_packing": False,
-                "dataset_processes": 1,
-                "special_tokens": {
-                    "pad_token": "<|endoftext|>",
-                },
-                "datasets": [
-                    {
-                        "path": "mhenrichsen/alpaca_2k_test",
-                        "type": "alpaca",
-                    },
-                    {
-                        "path": "tatsu-lab/alpaca",
-                        "type": "alpaca",
-                    },
-                ],
-                "test_datasets": [
-                    {
-                        "path": "mhenrichsen/alpaca_2k_test",
-                        "type": "alpaca",
-                        "split": "train",
-                    },
-                    {
-                        "path": "tatsu-lab/alpaca",
-                        "type": "alpaca",
-                        "split": "train",
-                    },
-                ],
-                # Streaming config
-                "streaming": True,
-                "eval_streaming": True,
-                "max_steps": 3,
-                # Different mixing for train vs eval
-                "dataset_mixing_strategy": "round_robin",
-                "eval_dataset_mixing_strategy": "weighted",
-                "eval_mixing_weights": [0.6, 0.4],
-                "micro_batch_size": 1,
-                "gradient_accumulation_steps": 1,
-                "output_dir": temp_dir,
-                "learning_rate": 0.00001,
-                "optimizer": "adamw_torch_fused",
-                "lr_scheduler": "cosine",
-                "save_safetensors": True,
-                "bf16": "auto",
-                "use_tensorboard": True,
-                "save_first_step": False,
-                "eval_steps": 3,  # Eval at the end
-            }
-        )
-
-        cfg = validate_config(cfg)
-        normalize_config(cfg)
-        dataset_meta = load_datasets(cfg=cfg)
-
-        train(cfg=cfg, dataset_meta=dataset_meta)
-        check_model_output_exists(temp_dir, cfg)
-
-        # Check both train and eval losses
-        check_tensorboard(
-            temp_dir + "/runs",
-            "train/train_loss",
-            2.5,
-            "Train Loss (%s) is too high",
-        )
-        check_tensorboard(
-            temp_dir + "/runs",
-            "eval/eval_loss",
-            2.5,
-            "Eval Loss (%s) is too high",
-        )
-
     def test_streaming_validation_error(self, temp_dir):
         """Test that pydantic validation catches invalid streaming configs"""