diff --git a/requirements-tpu.txt b/requirements-tpu.txt
index 725b1a2e4a580..d999e8f1c90ec 100644
--- a/requirements-tpu.txt
+++ b/requirements-tpu.txt
@@ -17,8 +17,9 @@ ray[default]
 --find-links https://storage.googleapis.com/libtpu-releases/index.html
 --find-links https://storage.googleapis.com/jax-releases/jax_nightly_releases.html
 --find-links https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
-
-torch==2.7.0.dev20250226+cpu
-torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.7.0.dev20250226+cxx11-cp39-cp39-linux_x86_64.whl ; python_version == "3.9"
-torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.7.0.dev20250226+cxx11-cp310-cp310-linux_x86_64.whl ; python_version == "3.10"
-torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.7.0.dev20250226+cxx11-cp311-cp311-linux_x86_64.whl ; python_version == "3.11"
+torch @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch-2.7.0.dev20250227%2Bcxx11-cp39-cp39-linux_x86_64.whl ; python_version == "3.9"
+torch @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch-2.7.0.dev20250227%2Bcxx11-cp310-cp310-linux_x86_64.whl ; python_version == "3.10"
+torch @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch-2.7.0.dev20250227%2Bcxx11-cp311-cp311-linux_x86_64.whl ; python_version == "3.11"
+torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.7.0.dev20250227%2Bcxx11-cp39-cp39-linux_x86_64.whl ; python_version == "3.9"
+torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.7.0.dev20250227%2Bcxx11-cp310-cp310-linux_x86_64.whl ; python_version == "3.10"
+torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.7.0.dev20250227%2Bcxx11-cp311-cp311-linux_x86_64.whl ; python_version == "3.11"
diff --git a/vllm/v1/worker/tpu_worker.py b/vllm/v1/worker/tpu_worker.py
index cbd2fe6edd81b..76b6297606c33 100644
--- a/vllm/v1/worker/tpu_worker.py
+++ b/vllm/v1/worker/tpu_worker.py
@@ -7,6 +7,7 @@ import torch
 import torch.distributed
 import torch.nn as nn
 import torch_xla.core.xla_model as xm
+import torch_xla.debug.profiler as xp
 import torch_xla.runtime as xr
 
 import vllm.envs as envs
@@ -65,6 +66,15 @@ class TPUWorker:
             from vllm.utils import init_cached_hf_modules
             init_cached_hf_modules()
 
+        self.profiler = None
+        if envs.VLLM_TORCH_PROFILER_DIR and self.rank < 1:
+            # For TPU, we can only have 1 active profiler session for 1 profiler
+            # server. So we only profile on rank0.
+            self.profile_dir = envs.VLLM_TORCH_PROFILER_DIR
+            logger.info("Profiling enabled. Traces will be saved to: %s",
+                        self.profile_dir)
+            self.profiler = xp.start_server(9012)
+
     def init_device(self):
         os.environ["PJRT_DEVICE"] = "TPU"
         torch.set_grad_enabled(False)
@@ -152,6 +162,15 @@ class TPUWorker:
         output = self.model_runner.execute_model(scheduler_output)
         return output if self.is_driver_worker else None
 
+    def profile(self, is_start: bool = True):
+        if self.rank < 1:
+            if self.profiler is None:
+                raise RuntimeError("Profiler is not enabled.")
+            if is_start:
+                xp.start_trace(self.profile_dir)
+            else:
+                xp.stop_trace()
+
     def load_model(self) -> None:
         self.model_runner.load_model()
 
diff --git a/vllm/worker/tpu_worker.py b/vllm/worker/tpu_worker.py
index 7903e81943c24..1a5eaba09b940 100644
--- a/vllm/worker/tpu_worker.py
+++ b/vllm/worker/tpu_worker.py
@@ -5,6 +5,7 @@ from typing import List, Optional, Tuple, Union
 
 import torch
 import torch_xla.core.xla_model as xm
+import torch_xla.debug.profiler as xp
 import torch_xla.runtime as xr
 
 import vllm.envs as envs
@@ -93,6 +94,27 @@ class TPUWorker(LoRANotSupportedWorkerBase, LocalOrDistributedWorkerBase):
                                      f"tp{world_size}_rank{rank}")
         xr.initialize_cache(per_rank_path, readonly=False)
 
+        self.profiler = None
+        if envs.VLLM_TORCH_PROFILER_DIR and self.rank < 1:
+            # For TPU, we can only have 1 active profiler session for 1 profiler
+            # server. So we only profile on rank0.
+            self.profile_dir = envs.VLLM_TORCH_PROFILER_DIR
+            logger.info("Profiling enabled. Traces will be saved to: %s",
+                        self.profile_dir)
+            self.profiler = xp.start_server(9012)
+
+    def start_profile(self):
+        if self.rank < 1:
+            if self.profiler is None:
+                raise RuntimeError("Profiler is not enabled.")
+            xp.start_trace(self.profile_dir)
+
+    def stop_profile(self):
+        if self.rank < 1:
+            if self.profiler is None:
+                raise RuntimeError("Profiler is not enabled.")
+            xp.stop_trace()
+
     def load_model(self):
         self.model_runner.load_model()