diff --git a/.buildkite/scripts/run_in_docker.sh b/.buildkite/scripts/run_in_docker.sh
index 85f2027215..6eb3ca9092 100755
--- a/.buildkite/scripts/run_in_docker.sh
+++ b/.buildkite/scripts/run_in_docker.sh
@@ -103,7 +103,6 @@ exec docker run \
   -e MODEL_IMPL_TYPE="$MODEL_IMPL_TYPE" \
   -e HF_TOKEN="$HF_TOKEN" \
   -e VLLM_XLA_CACHE_PATH="$DOCKER_HF_HOME/.cache/jax_cache" \
-  -e VLLM_USE_V1=1 \
   -e VLLM_XLA_CHECK_RECOMPILATION=1 \
   ${QUANTIZATION:+-e QUANTIZATION="$QUANTIZATION"} \
   ${NEW_MODEL_DESIGN:+-e NEW_MODEL_DESIGN="$NEW_MODEL_DESIGN"} \
diff --git a/scripts/vllm/integration/test_accuracy.py b/scripts/vllm/integration/test_accuracy.py
index 2c4e666f8c..421196a0e2 100644
--- a/scripts/vllm/integration/test_accuracy.py
+++ b/scripts/vllm/integration/test_accuracy.py
@@ -70,9 +70,7 @@ def test_lm_eval_accuracy_v1_engine(monkeypatch: pytest.MonkeyPatch,
     elif tp_size < 1 or tp_size > 8:
         raise ValueError
 
-    with monkeypatch.context() as m:
-        m.setenv("VLLM_USE_V1", "1")
-
+    with monkeypatch.context() as _:
         more_args = None
         if current_platform.is_tpu():
             more_args = "max_model_len=2048,max_num_seqs=64"
@@ -104,9 +102,7 @@ def test_lm_eval_accuracy_v1_engine_fp8_kv_cache(
     elif tp_size < 1 or tp_size > 8:
         raise ValueError
 
-    with monkeypatch.context() as m:
-        m.setenv("VLLM_USE_V1", "1")
-
+    with monkeypatch.context() as _:
         more_args = None
         if current_platform.is_tpu():
             more_args = "max_model_len=2048,max_num_seqs=128,kv_cache_dtype=fp8"
diff --git a/tests/executors/test_ray_distributed_executor.py b/tests/executors/test_ray_distributed_executor.py
index a0bfbbaaf6..b50d3f537a 100644
--- a/tests/executors/test_ray_distributed_executor.py
+++ b/tests/executors/test_ray_distributed_executor.py
@@ -61,7 +61,6 @@ def test_init_executor_basic_flow(self, mock_wait_until_pg_ready,
         # --- Setup mocks ---
         mock_envs.VLLM_USE_RAY_COMPILED_DAG = True
         mock_envs.VLLM_USE_RAY_SPMD_WORKER = True
-        mock_envs.VLLM_USE_V1 = True
         mock_envs.VLLM_RAY_BUNDLE_INDICES = ""
 
         mock_platform.ray_device_key = "TPU"
diff --git a/tpu_inference/executors/ray_distributed_executor.py b/tpu_inference/executors/ray_distributed_executor.py
index f1f055eece..423ffa23e7 100644
--- a/tpu_inference/executors/ray_distributed_executor.py
+++ b/tpu_inference/executors/ray_distributed_executor.py
@@ -97,7 +97,6 @@ def _init_executor(self) -> None:
         self.input_encoder = msgspec.msgpack.Encoder(enc_hook=_encode_hook)
         self.output_decoder = msgspec.msgpack.Decoder(
             Optional[List[SamplerOutput]])
-        self.use_v1 = envs.VLLM_USE_V1
 
         self.pp_locks: Optional[List[asyncio.Lock]] = None
 
diff --git a/tpu_inference/mock/vllm_envs.py b/tpu_inference/mock/vllm_envs.py
index 82084d1fc5..1a938002a6 100644
--- a/tpu_inference/mock/vllm_envs.py
+++ b/tpu_inference/mock/vllm_envs.py
@@ -91,7 +91,6 @@
     VLLM_ALLOW_RUNTIME_LORA_UPDATING: bool = False
     VLLM_SKIP_P2P_CHECK: bool = False
     VLLM_DISABLED_KERNELS: list[str] = []
-    VLLM_USE_V1: bool = True
     VLLM_ROCM_USE_AITER: bool = False
     VLLM_ROCM_USE_AITER_PAGED_ATTN: bool = False
     VLLM_ROCM_USE_AITER_LINEAR: bool = True
@@ -725,10 +724,6 @@ def get_vllm_port() -> Optional[int]:
     lambda: [] if "VLLM_DISABLED_KERNELS" not in os.environ else os.environ[
         "VLLM_DISABLED_KERNELS"].split(","),
 
-    # If set, use the V1 code path.
-    "VLLM_USE_V1":
-    lambda: bool(int(os.getenv("VLLM_USE_V1", "1"))),
-
     # Disable aiter ops unless specifically enabled.
     # Acts as a parent switch to enable the rest of the other operations.
     "VLLM_ROCM_USE_AITER":
@@ -1180,15 +1175,6 @@ def is_set(name: str):
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 
-def set_vllm_use_v1(use_v1: bool):
-    if is_set("VLLM_USE_V1"):
-        raise ValueError(
-            "Should not call set_vllm_use_v1() if VLLM_USE_V1 is set "
-            "explicitly by the user. Please raise this as a Github "
-            "Issue and explicitly set VLLM_USE_V1=0 or 1.")
-    os.environ["VLLM_USE_V1"] = "1" if use_v1 else "0"
-
-
 def compute_hash() -> str:
     """
     WARNING: Whenever a new key is added to this environment
diff --git a/tpu_inference/platforms/tpu_platform.py b/tpu_inference/platforms/tpu_platform.py
index 0f47ed60fb..c19d673526 100644
--- a/tpu_inference/platforms/tpu_platform.py
+++ b/tpu_inference/platforms/tpu_platform.py
@@ -88,7 +88,7 @@ def get_device_total_memory(cls, device_id: int = 0) -> int:
 
     @classmethod
     def is_async_output_supported(cls, enforce_eager: Optional[bool]) -> bool:
-        return not vllm_envs.VLLM_USE_V1
+        return False
 
     @classmethod
     def get_punica_wrapper(cls) -> str:
@@ -119,8 +119,6 @@ def _initialize_sharding_config(cls, vllm_config: VllmConfig) -> None:
 
     @classmethod
     def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
-        if not vllm_envs.VLLM_USE_V1:
-            raise RuntimeError("VLLM_USE_V1=1 must be set for JAX backend.")
 
         if vllm_envs.VLLM_TPU_USING_PATHWAYS:
             assert not vllm_envs.VLLM_ENABLE_V1_MULTIPROCESSING, (
@@ -165,22 +163,19 @@ def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
             vllm_config.model_config.dtype = j2t_dtype(
                 vllm_config.model_config.dtype.dtype)
 
-        if vllm_envs.VLLM_USE_V1:
-            # TODO(cuiq): remove this dependency.
-            from vllm.v1.attention.backends.pallas import \
-                PallasAttentionBackend
-            cache_config.block_size = PallasAttentionBackend.get_page_size(
-                vllm_config)  # type: ignore[assignment]
-            min_page_size = PallasAttentionBackend.get_min_page_size(
-                vllm_config)
-            if min_page_size > cache_config.block_size:
-                logger.warning(
-                    "Increase the page size from %s to %s to make sure there's"
-                    "no SMEM OOM",
-                    cache_config.block_size,
-                    min_page_size,
-                )
-                cache_config.block_size = min_page_size  # type: ignore[assignment]
+        # TODO(cuiq): remove this dependency.
+        from vllm.v1.attention.backends.pallas import PallasAttentionBackend
+        cache_config.block_size = PallasAttentionBackend.get_page_size(
+            vllm_config)  # type: ignore[assignment]
+        min_page_size = PallasAttentionBackend.get_min_page_size(vllm_config)
+        if min_page_size > cache_config.block_size:
+            logger.warning(
+                "Increase the page size from %s to %s to make sure there's"
+                "no SMEM OOM",
+                cache_config.block_size,
+                min_page_size,
+            )
+            cache_config.block_size = min_page_size  # type: ignore[assignment]
 
         parallel_config = vllm_config.parallel_config
         scheduler_config = vllm_config.scheduler_config
@@ -251,9 +246,6 @@ def validate_request(
         """Raises if this request is unsupported on this platform"""
 
         if isinstance(params, SamplingParams):
-            if params.structured_outputs is not None and not vllm_envs.VLLM_USE_V1:
-                raise ValueError("Structured output is not supported on "
-                                 f"{cls.device_name} V0.")
             if params.sampling_type == SamplingType.RANDOM_SEED:
                 raise ValueError("JAX does not support per-request seed.")