diff --git a/vllm/collect_env.py b/vllm/collect_env.py
index c042fc1d7..0cf5681bc 100644
--- a/vllm/collect_env.py
+++ b/vllm/collect_env.py
@@ -146,14 +146,6 @@ def run_and_parse_first_match(run_lambda, command, regex):
     return match.group(1)
 
 
-def run_and_return_first_line(run_lambda, command):
-    """Run command using run_lambda and returns first line if output is not empty."""
-    rc, out, _ = run_lambda(command)
-    if rc != 0:
-        return None
-    return out.split("\n")[0]
-
-
 def get_conda_packages(run_lambda, patterns=None):
     if patterns is None:
         patterns = DEFAULT_CONDA_PATTERNS
diff --git a/vllm/compilation/fx_utils.py b/vllm/compilation/fx_utils.py
index 5c2e7ac93..a87ffea78 100644
--- a/vllm/compilation/fx_utils.py
+++ b/vllm/compilation/fx_utils.py
@@ -18,21 +18,6 @@ def is_auto_func(node: fx.Node, op: OpOverload) -> bool:
     return is_func(node, auto_functionalized) and node.args[0] == op
 
 
-# Returns the first specified node with the given op (if it exists)
-def find_specified_fn_maybe(nodes: Iterable[fx.Node], op: OpOverload) -> fx.Node | None:
-    for node in nodes:
-        if node.target == op:
-            return node
-    return None
-
-
-# Returns the first specified node with the given op
-def find_specified_fn(nodes: Iterable[fx.Node], op: OpOverload) -> fx.Node:
-    node = find_specified_fn_maybe(nodes, op)
-    assert node is not None, f"Could not find {op} in nodes {nodes}"
-    return node
-
-
 # Returns the first auto_functionalized node with the given op (if it exists)
 def find_auto_fn_maybe(nodes: Iterable[fx.Node], op: OpOverload) -> fx.Node | None:
     for node in nodes:
diff --git a/vllm/config/utils.py b/vllm/config/utils.py
index e8c866f02..bd2a741e3 100644
--- a/vllm/config/utils.py
+++ b/vllm/config/utils.py
@@ -14,7 +14,6 @@ from dataclasses import MISSING, Field, field, fields, is_dataclass
 from itertools import pairwise
 from typing import TYPE_CHECKING, Any, Protocol, TypeVar, cast
 
-import regex as re
 import torch
 from pydantic import ConfigDict
 from pydantic.dataclasses import dataclass
@@ -144,34 +143,6 @@ def getattr_iter(
     return default_factory() if default_factory is not None else default
 
 
-def contains_object_print(text: str) -> bool:
-    """
-    Check if the text looks like a printed Python object, e.g.
-    contains any substring matching the pattern: "at 0xFFFFFFF>"
-    We match against 0x followed by 2-16 hex chars (there's
-    a max of 16 on a 64-bit system).
-
-    Args:
-        text (str): The text to check
-
-    Returns:
-        result (bool): `True` if a match is found, `False` otherwise.
-    """
-    pattern = r"at 0x[a-fA-F0-9]{2,16}>"
-    match = re.search(pattern, text)
-    return match is not None
-
-
-def assert_hashable(text: str) -> bool:
-    if not contains_object_print(text):
-        return True
-    raise AssertionError(
-        f"vLLM tried to hash some configs that may have Python objects ids "
-        f"in them. This is a bug, please file an issue. "
-        f"Text being hashed: {text}"
-    )
-
-
 def get_attr_docs(cls: type[Any]) -> dict[str, str]:
     """
     Get any docstrings placed after attribute assignments in a class body.
@@ -354,31 +325,6 @@ def hash_factors(items: dict[str, object]) -> str:
     return hashlib.sha256(json.dumps(items, sort_keys=True).encode()).hexdigest()
 
 
-def handle_deprecated(
-    config: ConfigT,
-    old_name: str,
-    new_name_or_names: str | list[str],
-    removal_version: str,
-) -> None:
-    old_val = getattr(config, old_name)
-    if old_val is None:
-        return
-
-    if isinstance(new_name_or_names, str):
-        new_names = [new_name_or_names]
-    else:
-        new_names = new_name_or_names
-
-    msg = (
-        f"{old_name} is deprecated and will be removed in {removal_version}. "
-        f"Use {', '.join(new_names)} instead."
-    )
-    logger.warning(msg)
-
-    for new_name in new_names:
-        setattr(config, new_name, old_val)
-
-
 @dataclass
 class Range:
     """