diff --git a/litellm/batch_completion/main.py b/litellm/batch_completion/main.py
index 7ec71dcd4bb..702dd194fda 100644
--- a/litellm/batch_completion/main.py
+++ b/litellm/batch_completion/main.py
@@ -1,29 +1,13 @@
-from collections.abc import Mapping
 from concurrent.futures import FIRST_COMPLETED, ThreadPoolExecutor, wait
 from typing import Final
 
 import litellm
 from litellm._logging import print_verbose
-from litellm.utils import get_model_info, get_optional_params
+from litellm.utils import get_optional_params
 
 from ..llms.vllm.completion import handler as vllm_handler
 
 
-def _model_info_for_batch(
-    *,
-    model: str,
-    custom_llm_provider: str | None,
-    kwargs: Mapping[str, object],
-) -> Mapping[str, object] | None:
-    from_kwargs: Final = kwargs.get("model_info")
-    if isinstance(from_kwargs, Mapping):
-        return from_kwargs
-    try:
-        return get_model_info(model=model, custom_llm_provider=custom_llm_provider)
-    except Exception:  # noqa: BLE001  # get_model_info raises Exception for unmapped models
-        return None
-
-
 def batch_completion(
     model: str,
     # Optional OpenAI params: see https://platform.openai.com/docs/api-reference/chat/create
@@ -95,13 +79,9 @@ def batch_completion(
             frequency_penalty=frequency_penalty,
             logit_bias=logit_bias,
             user=user,
+            # params to identify the model
             model=model,
             custom_llm_provider=custom_llm_provider,
-            model_info=_model_info_for_batch(
-                model=model,
-                custom_llm_provider=custom_llm_provider,
-                kwargs=kwargs,
-            ),
         )
         results = vllm_handler.batch_completions(
             model=model,