diff --git a/.github/container/Dockerfile.base b/.github/container/Dockerfile.base
index 023576cb5..9f0851897 100644
--- a/.github/container/Dockerfile.base
+++ b/.github/container/Dockerfile.base
@@ -1,8 +1,8 @@
 # syntax=docker/dockerfile:1-labs
-ARG BASE_IMAGE=nvidia/cuda:12.5.0-devel-ubuntu22.04
+ARG BASE_IMAGE=nvidia/cuda:12.6.1-devel-ubuntu22.04
 ARG GIT_USER_NAME="JAX Toolbox"
 ARG GIT_USER_EMAIL=jax@nvidia.com
-ARG CLANG_VERSION=17
+ARG CLANG_VERSION=18
 
 ###############################################################################
 ## Obtain GCP's NCCL TCPx plugin
diff --git a/.github/container/Dockerfile.jax b/.github/container/Dockerfile.jax
index c85bee347..726656a7a 100644
--- a/.github/container/Dockerfile.jax
+++ b/.github/container/Dockerfile.jax
@@ -62,6 +62,7 @@ pip install ninja && rm -rf ~/.cache/pip
 # TransformerEngine now needs JAX at build time
 git-clone.sh ${URLREF_TRANSFORMER_ENGINE} ${SRC_PATH_TRANSFORMER_ENGINE}
 pushd ${SRC_PATH_TRANSFORMER_ENGINE}
+export NVTE_BUILD_THREADS_PER_JOB=8
 python setup.py bdist_wheel && rm -rf build
 ls "${SRC_PATH_TRANSFORMER_ENGINE}/dist"
 EOF
diff --git a/.github/container/build-jax.sh b/.github/container/build-jax.sh
index fa4c055b8..8ff65ca99 100755
--- a/.github/container/build-jax.sh
+++ b/.github/container/build-jax.sh
@@ -316,6 +316,9 @@ pip --disable-pip-version-check install -e ${BUILD_PATH_JAXLIB}/jaxlib -e ${BUIL
 #  jaxlib                  0.4.32.dev20240808           /opt/jaxlibs/jaxlib
 pip list | grep jax
 
+# Ensure directories are readable by all for non-root users
+chmod 755 $BUILD_PATH_JAXLIB/*
+
 ## Cleanup
 
 pushd $SRC_PATH_JAX
diff --git a/.github/container/install-nsight.sh b/.github/container/install-nsight.sh
index 73aee4163..f3e4e0715 100755
--- a/.github/container/install-nsight.sh
+++ b/.github/container/install-nsight.sh
@@ -17,11 +17,12 @@ apt-get clean
 
 rm -rf /var/lib/apt/lists/*
 
-NSYS202451=/opt/nvidia/nsight-systems-cli/2024.5.1
-if [[ -d "${NSYS202451}" ]]; then
-  # * can match at least sbsa-armv8 and x86
-  (cd ${NSYS202451}/target-linux-*/python/packages && git apply < /opt/nvidia/nsys-2024.5-tid-export.patch)
-fi
+for NSYS in /opt/nvidia/nsight-systems-cli/2024.5.1 /opt/nvidia/nsight-systems-cli/2024.6.1; do
+  if [[ -d "${NSYS}" ]]; then
+    # * can match at least sbsa-armv8 and x86
+    (cd ${NSYS}/target-linux-*/python/packages && git apply < /opt/nvidia/nsys-2024.5-tid-export.patch)
+  fi
+done
 
 # Install extra dependencies needed for `nsys recipe ...` commands. These are
 # used by the nsys-jax wrapper script.
diff --git a/.github/container/jax_nsys/python/jax_nsys/jax_nsys/analysis.py b/.github/container/jax_nsys/python/jax_nsys/jax_nsys/analysis.py
index 9e3aaee4f..4e72a33fb 100644
--- a/.github/container/jax_nsys/python/jax_nsys/jax_nsys/analysis.py
+++ b/.github/container/jax_nsys/python/jax_nsys/jax_nsys/analysis.py
@@ -6,7 +6,7 @@
 import pathlib
 from typing import Any
 
-from .protobuf import HloProto, xla_module_metadata
+from .protobuf import HloProto, _host_memory_space, xla_module_metadata
 from .utils import make_child_mask, ProfilerData
 
 pd.options.mode.copy_on_write = True
@@ -38,6 +38,11 @@ def align_profiler_data_timestamps(
     # Determine which collective size will be used for the alignment
     num_profiled_devices = len(comm_df.index.get_level_values("Device").unique())
     max_collective_size = comm_df["CollectiveSize"].max()
+    if max_collective_size == 1:
+        print(
+            f"WARNING: cannot align {num_profiled_devices} devices because max collective size is 1"
+        )
+        return frames, {}
     assert (
         num_profiled_devices == max_collective_size
     ), f"Aligning {num_profiled_devices} using collectives of size {max_collective_size} is not implemented"
@@ -193,13 +198,51 @@ def _get_message_size(
             "all-to-all",
             "collective-broadcast",
             "collective-permute-start",
+            "dynamic-slice",
+            "dynamic-update-slice",
             "reduce-scatter",
         }
     ), f"{instruction}: message size calculation for {comm_inst.opcode} has not yet been validated"
+
+    def _byte_size(inst) -> int:
+        size_bits = math.prod(
+            inst.shape.dimensions,
+            start=element_type_width(inst.shape.element_type),
+        )
+        size_bytes, rem = divmod(size_bits, 8)
+        assert rem == 0
+        return size_bytes
+
     if comm_inst.opcode == "collective-permute-start":
         # See https://openxla.org/xla/operation_semantics#collectivepermute, which
         # generates pair-wise send+recv between devices
         collective_size = 2
+    elif comm_inst.opcode in {"dynamic-slice", "dynamic-update-slice"}:
+        # Label host-device transfers orchestrated by dynamic[-update]-slice as single
+        # device collectives.
+        collective_size = 1
+        if comm_inst.opcode == "dynamic-update-slice":
+            # For dynamic-update-slice the second operand is the one being copied
+            _, src_inst = module_proto.find_instruction_by_id(comm_inst.operand_ids[1])
+            transfer_size = _byte_size(src_inst.proto())
+        else:
+            # For dynamic-slice the return type size is the transfer size
+            assert comm_inst.opcode == "dynamic-slice"
+            _, src_inst = module_proto.find_instruction_by_id(comm_inst.operand_ids[0])
+            transfer_size = _byte_size(comm_inst)
+        dest_on_host = _host_memory_space(comm_inst)
+        src_on_host = _host_memory_space(src_inst.proto())
+        assert src_on_host != dest_on_host, (
+            'dynamic[-update]-slice is only considered is only "communication" if it '
+            "represents a host-device transfer"
+        )
+        return (
+            transfer_size,
+            "device-to-host" if dest_on_host else "host-to-device",
+            1,  # collective size
+            1.0,  # bw_correction
+            1.0,  # bus_correction
+        )
     else:
         # replica_groups is something like {{0,1},{4,5},{2,3},{6,7}}, if there are 8
         # devices that are doing pair-wise collectives
@@ -220,17 +263,12 @@ def _get_message_size(
     total_msg_size = 0
     for operand_id in comm_inst.operand_ids:
         _, operand = module_proto.find_instruction_by_id(operand_id)
-        msg_size_bits = math.prod(
-            operand.proto().shape.dimensions,
-            start=element_type_width(operand.proto().shape.element_type),
-        )
+        msg_size_bytes = _byte_size(operand.proto())
         if comm_inst.opcode == "reduce-scatter":
             # NCCL's convention is that the message size of a reduce-scatter is the size of output buffer:
             # https://github.com/NVIDIA/nccl/blob/ab2b89c4c339bd7f816fbc114a4b05d386b66290/src/collectives.cc#L122
-            msg_size_bits, rem = divmod(msg_size_bits, collective_size)
+            msg_size_bytes, rem = divmod(msg_size_bytes, collective_size)
             assert rem == 0
-        msg_size_bytes, rem = divmod(msg_size_bits, 8)
-        assert rem == 0
         total_msg_size += msg_size_bytes
 
     collective = comm_inst.opcode.removesuffix("-start")
diff --git a/.github/container/jax_nsys/python/jax_nsys/jax_nsys/data_loaders.py b/.github/container/jax_nsys/python/jax_nsys/jax_nsys/data_loaders.py
index 6c25cb2ee..d6e4464bd 100644
--- a/.github/container/jax_nsys/python/jax_nsys/jax_nsys/data_loaders.py
+++ b/.github/container/jax_nsys/python/jax_nsys/jax_nsys/data_loaders.py
@@ -103,6 +103,9 @@ def is_communication(row):
     return _calculate_overlap(thunk_df)
 
 
+compile_prefix = "XlaCompile:#module="
+
+
 def _load_nvtx_gpu_proj_trace_single(
     prefix: pathlib.Path,
     file: pathlib.Path,
@@ -305,10 +308,21 @@ def _load_nvtx_gpu_proj_trace_single(
         unique_pid_tid_pairs = module_df.loc[:, ("PID", "TID")].drop_duplicates()
         if len(unique_pid_tid_pairs) == 1:
             main_pid_tid_candidates.add(tuple(unique_pid_tid_pairs.iloc[0]))
+    # If the profile only includes N>1 modules, we may still be able to identify the
+    # main thread as the one responsible for XlaCompile ranges projected onto the GPU
+    # timeline
+    compile_ranges = df.loc[~all_thunks, "Name"].str.startswith(
+        tsl_prefix + compile_prefix
+    )
+    compile_range_ids = compile_ranges[compile_ranges].index
+    unique_pid_tid_pairs = df.loc[compile_range_ids, ("PID", "TID")].drop_duplicates()
+    if len(unique_pid_tid_pairs) == 1:
+        main_pid_tid_candidates.add(tuple(unique_pid_tid_pairs.iloc[0]))
     assert len(main_pid_tid_candidates) < 2
     if len(main_pid_tid_candidates) == 1:
         # Possibly not correct if len(device_by_pid_tid) > 1
         assert len(device_by_pid_tid) > 0
+        # Associate the main thread with the 0th device in device_by_pid_tid
         main_thread_df = device_by_pid_tid.iloc[:1]
         main_thread_df.index = pd.MultiIndex.from_tuples(
             main_pid_tid_candidates, names=["PID", "TID"]
@@ -425,16 +439,13 @@ def _load_nvtx_gpu_proj_trace(
     return output
 
 
-compile_prefix = "TSL:XlaCompile:#module="
-
-
 def _splice_parallel_ranges(compile_df: pd.DataFrame) -> pd.DataFrame:
     # When parallel compilation is enabled, we end up with worker threads that
     # emit NVTX ranges but which are not accounted for in the RangeStack tree.
     # Splice these in under the relevant XlaCompile ranges in the RangeStack tree and
     # drop everything else.
     retain_mask = pd.Series(False, index=compile_df.index)
-    compile_mask = compile_df["Name"].str.startswith(compile_prefix)
+    compile_mask = compile_df["Name"].str.startswith("TSL:" + compile_prefix)
     for compile_range in compile_df[compile_mask].itertuples():
         # Identify the slice of `compile_df` that overlaps in time with this XlaCompile
         # range
diff --git a/.github/container/jax_nsys/python/jax_nsys/jax_nsys/protobuf.py b/.github/container/jax_nsys/python/jax_nsys/jax_nsys/protobuf.py
index ef74165fd..4feae6038 100644
--- a/.github/container/jax_nsys/python/jax_nsys/jax_nsys/protobuf.py
+++ b/.github/container/jax_nsys/python/jax_nsys/jax_nsys/protobuf.py
@@ -1,10 +1,13 @@
-from collections import defaultdict
 import functools
 import lzma
 import pathlib
 import typing
 
 
+def _host_memory_space(inst):
+    return inst.shape.layout.memory_space == 5
+
+
 class StackFrame(typing.NamedTuple):
     column: int
     file: str
@@ -25,6 +28,35 @@ def __init__(self, wrapped_hlo_proto, proto):
         # proto representing the actual collective, which will be different if the
         # async launch is handled by an async-start op
         # TODO: can any of copy-start, custom-call, recv, send represent communication?
+        # This also aims to identify, and (for now) flag as communication, kernels that
+        # implement device-to-host and host-to-device copies for memory offloading.
+        # For example, a device-to-host offload might look like
+        #   computation {
+        #     ...
+        #     ROOT r1 = bf16[2,8,128,2048]{3,2,1,0:S(5)} dynamic-update-slice(...)
+        #   }
+        #   async_computation {
+        #     ...
+        #     ROOT r2 = bf16[2,8,128,2048]{3,2,1,0:S(5)} fusion(...), calls=computation
+        #   }
+        #   start = (...) async-start(...), calls=async_computation
+        # where the :S(5) annotation shows that a buffer is in host memory.
+        # A host-to-device load might look like
+        #   computation {
+        #     param_0 = bf16[2,8,128,2048]{3,2,1,0:S(5)} parameter(0)
+        #     ...
+        #     ROOT r1 = bf16[2,8,128,2048]{3,2,1,0} dynamic-slice(param_0, ...)
+        #   }
+        #   async_computation {
+        #     param_0 = bf16[2,8,128,2048]{3,2,1,0:S(5)} parameter(0)
+        #     ...
+        #     ROOT r2 = bf16[2,8,128,2048]{3,2,1,0} fusion(param_0, ...), calls=computation
+        #   }
+        #   start = (...) async-start(...), calls=async_computation
+        # where the :S(5) memory space annotation is in a parameter instead of in the
+        # return value.
+        # For now, handling host-device kernels as single-device "collective"
+        # communication should be sufficient.
         self._comm_proto = None
         comm_opcodes = {
             "all-gather",
@@ -39,25 +71,50 @@ def __init__(self, wrapped_hlo_proto, proto):
             "all-reduce-start",
             "collective-permute-start",
         }
+
+        def _is_offloading_instruction(inst):
+            host_dest = _host_memory_space(inst)
+
+            def _host_operand(i):
+                _, op = wrapped_hlo_proto.find_instruction_by_id(inst.operand_ids[i])
+                return _host_memory_space(op.proto())
+
+            if inst.opcode == "dynamic-slice" and host_dest != _host_operand(0):
+                return True
+            elif (
+                inst.opcode == "dynamic-update-slice"
+                and host_dest == _host_operand(0)
+                and host_dest != _host_operand(1)
+            ):
+                return True
+            return False
+
         if self._proto.opcode in comm_opcodes | comm_start_opcodes:
             self._comm_proto = self._proto
-        elif self._proto.opcode == "async-start":
+        elif self._proto.opcode in {"async-start", "fusion"}:
+            # fusion example:
+            #   computation {
+            #     param_0 = f32[...]{...:S(5)} parameter(0)
+            #     ...
+            #     ROOT dus = f32[...]{...:S(5)} dynamic-update-slice(param_0, ...)
+            #   }
+            #   inst = f32[256,128,128]{2,1,0:S(5)} fusion(...), calls=computation
             # This might be thinly wrapping an opcode in `comm_opcodes`
-            other_opcodes = defaultdict(int)
-            for called_id in self._proto.called_computation_ids:
-                for called_inst in wrapped_hlo_proto.find_computation(
-                    called_id
-                ).instructions:
-                    if called_inst.opcode in comm_opcodes:
+            def _visit_computation(computation_id):
+                computation = wrapped_hlo_proto.find_computation(computation_id)
+                for called_inst in computation.instructions:
+                    for called_id in called_inst.called_computation_ids:
+                        _visit_computation(called_id)
+                    if called_inst.opcode in comm_opcodes or _is_offloading_instruction(
+                        called_inst
+                    ):
                         assert (
                             self._comm_proto is None
                         ), f"Found {called_inst.opcode} child having already found {self._comm_proto.opcode}"
                         self._comm_proto = called_inst
-                    else:
-                        other_opcodes[called_inst.opcode] += 1
-            assert (
-                other_opcodes.keys() == {"parameter"}
-            ), f"async-start op {self._proto.name} wrapped too many opcode types ({dict(other_opcodes)}) in addition to {self._comm_proto}"
+
+            for called_id in self._proto.called_computation_ids:
+                _visit_computation(called_id)
 
     def communication_proto(self):
         return self._comm_proto
@@ -68,12 +125,7 @@ def is_communication(self) -> bool:
         a little more complicated than you might hope, because async communications are
         not handled uniformly.
         """
-        if self._comm_proto is None:
-            return False
-        assert (
-            self._comm_proto.channel_id != 0
-        ), f"Got channel_id={self._comm_proto.channel_id} for {self._comm_proto.name}"
-        return True
+        return self._comm_proto is not None
 
     def proto(self):
         """
diff --git a/.github/container/manifest.yaml b/.github/container/manifest.yaml
index 60ef1a001..e9d30a3bc 100644
--- a/.github/container/manifest.yaml
+++ b/.github/container/manifest.yaml
@@ -177,3 +177,8 @@ orbax-checkpoint:
   tracking_ref: main
   latest_verified_commit: 16c2d409e365576284dbaf190ac002b24c1f927f
   mode: pip-vcs
+pathwaysutils:
+  url: https://github.com/google/pathways-utils.git
+  tracking_ref: main
+  latest_verified_commit: 359776d454940ffaa337c36d1df16308d44a95a9
+  mode: pip-vcs
diff --git a/.github/container/test-maxtext.sh b/.github/container/test-maxtext.sh
index 164fa5912..0dc26c8c1 100755
--- a/.github/container/test-maxtext.sh
+++ b/.github/container/test-maxtext.sh
@@ -223,7 +223,7 @@ export NVTE_FUSED_ATTN=${ENABLE_FUSED_ATTN}
 export XLA_PYTHON_CLIENT_MEM_FRACTION=${MEM_FRACTION}
 export CUDA_DEVICE_MAX_CONNECTIONS=1
 
-export BASE_XLA_FLAGS=${BASE_XLA_FLAGS:---xla_gpu_enable_latency_hiding_scheduler=true 
+export BASE_XLA_FLAGS=${BASE_XLA_FLAGS:---xla_gpu_enable_latency_hiding_scheduler=true
                 --xla_gpu_enable_triton_gemm=false
                 --xla_gpu_graph_level=0 
                 --xla_gpu_all_reduce_combine_threshold_bytes=1073741824 
@@ -232,8 +232,7 @@ export BASE_XLA_FLAGS=${BASE_XLA_FLAGS:---xla_gpu_enable_latency_hiding_schedule
                 --xla_gpu_enable_pipelined_all_gather=true 
                 --xla_gpu_enable_pipelined_reduce_scatter=true 
                 --xla_gpu_enable_pipelined_all_reduce=true 
-                --xla_gpu_enable_while_loop_double_buffering=true
-                --xla_gpu_enable_triton_softmax_fusion=false 
+                --xla_gpu_enable_while_loop_double_buffering=true 
                 --xla_gpu_enable_all_gather_combine_by_dim=false 
                 --xla_gpu_enable_reduce_scatter_combine_by_dim=false 
                 --xla_disable_hlo_passes=rematerialization}
diff --git a/.github/container/test-pax.sh b/.github/container/test-pax.sh
index 2b33f53f7..46ce6ae73 100755
--- a/.github/container/test-pax.sh
+++ b/.github/container/test-pax.sh
@@ -15,7 +15,8 @@ usage() {
     echo "  -a, --additional-args      Additional fiddle args to pass to paxml/main.py"
     echo "  -b, --batch-per-gpu        Batch size per GPU, defaults to 4."
     echo "  --dtype                    Batch size, defaults to bfloat16."
-    echo "  --enable-te                If set, will run with env var ENABLE_TE=1." 
+    echo "  --enable-te                If set, will run with env var ENABLE_TE=1."
+    echo "  --enable-cudnn-fa          If set, will use cudnn fa."
     echo "  --enable-dropout           If set, will set DROPOUT_PROB to 0.1."
     echo "  --disable-fused-attn       Whether disable TE fused attention."
     echo "  --model-type               One of 126M, 5B, LLaMA70BProxy. Defaults to 126M"
@@ -26,13 +27,13 @@ usage() {
     echo "  --data-parallel            Data parallelism to use. Defaults to 1."
     echo "  --fsdp                     Fully-sharded data parallelism to use. Defaults to 1."
     echo "  --tensor-parallel          Tensor parallelism to use. Defaults to 1."
-    echo "  --pipeline-parallel        Pipeline parallelism to use. Defaults to 1 for no pipelining." 
+    echo "  --pipeline-parallel        Pipeline parallelism to use. Defaults to 1 for no pipelining."
     echo "  -n, --nodes                Number of nodes."
     echo "  -h, --help                 Print usage."
     exit $1
 }
 
-args=$(getopt -o a:b:s:o:n:h --long additional-args:,batch-per-gpu:,dtype:,enable-te,enable-dropout,disable-fused-attn,model-type:,evaluate,steps:,help,multiprocess,output:,data-parallel:,fsdp:,tensor-parallel:,pipeline-parallel:,nodes: -- "$@")
+args=$(getopt -o a:b:s:o:n:h --long additional-args:,batch-per-gpu:,dtype:,enable-te,enable-cudnn-fa,enable-dropout,disable-fused-attn,model-type:,evaluate,steps:,help,multiprocess,output:,data-parallel:,fsdp:,tensor-parallel:,pipeline-parallel:,nodes: -- "$@")
 if [[ $? -ne 0 ]]; then
     exit $1
 fi
@@ -50,6 +51,7 @@ TP=1
 PP=1
 NODES=1
 ENABLE_TE=0
+ENABLE_CUDNN_FA=0
 MODEL_TYPE=126M
 NVTE_FUSED_ATTN=1
 DROPOUT=0
@@ -75,6 +77,10 @@ while [ : ]; do
             ENABLE_TE=1
             shift 1
             ;;
+        --enable-cudnn-fa)
+            ENABLE_CUDNN_FA=1
+            shift 1
+            ;;
         --enable-dropout)
             DROPOUT='0.1'
             shift 1
@@ -128,7 +134,7 @@ while [ : ]; do
             ;;
         --)
             shift;
-            break 
+            break
             ;;
         *)
             echo "UNKNOWN OPTION $1"
@@ -149,6 +155,7 @@ print_var NGPUS
 print_var OUTPUT
 print_var MULTIPROCESS
 print_var ENABLE_TE
+print_var ENABLE_CUDNN_FA
 print_var NVTE_FUSED_ATTN
 print_var EVALUATE
 print_var DROPOUT
@@ -196,10 +203,10 @@ if dcn_factor > 1:
   if dp % dcn_factor == 0:
     dcn_dp = dcn_factor
     dp = int(dp / dcn_factor)
-  elif fsdp % dcn_factor == 0: 
+  elif fsdp % dcn_factor == 0:
     dcn_fsdp = dcn_factor
     fsdp = int(fsdp / dcn_factor)
-  elif pp % dcn_factor == 0: 
+  elif pp % dcn_factor == 0:
     dcn_pp = dcn_factor
     pp = int(pp / dcn_factor)
 
@@ -209,12 +216,12 @@ class GPT126MPP(TransformerLmSpmdPipelineAdam):
   USE_REPEATED_LAYER = False
   ICI_MESH_SHAPE = [64,1,1]
   MAX_STEPS = 600000
-  
+
   MAX_SEQ_LEN = 2048
   VOCAB_SIZE = 50304
   PACKED_INPUT = True
   PERCORE_BATCH_SIZE = 4
-  
+
   NUM_LAYERS = 12
   NUM_HEADS = 12
   MODEL_DIMS = 768
@@ -223,14 +230,14 @@ class GPT126MPP(TransformerLmSpmdPipelineAdam):
 
   TRAINABLE_POSITION_EMB = True
   TRAINABLE_PE_MAX_SEQ_LEN = MAX_SEQ_LEN
-  
+
   USE_BIAS = True
   LAYERNORM_EPSILON = 1e-5
   ATTEN_LOGIT_CAP = -1.0
   INIT_STD = 0.023
   SOFTMAX_INIT_STD = 0.023
   ACTIVATION_CLS = layers.GELU
-    
+
   ## optimizer-related
   ADAM_BETA1 = 0.9
   ADAM_BETA2 = 0.95
@@ -255,7 +262,7 @@ class GPT126MPP(TransformerLmSpmdPipelineAdam):
   ## disable eval to avoid including eval
   ## in steps/sec calculation
   EVAL_INTERVAL_STEPS = 100000
-  
+
   def task(self):
     task_p = super().task()
     task_p = configure_gpt3_task(self, task_p)
@@ -263,7 +270,7 @@ class GPT126MPP(TransformerLmSpmdPipelineAdam):
     task_p.train.num_train_steps = self.MAX_STEPS
 
     model_p = task_p.model
-    
+
     ### compute layernorm reductions in fp32. Needed for stable training on GPUs
     stacked_p = model_p.lm_tpl.stacked_transformer_tpl
     if stacked_p.cls == layers.PipelinedTransformer:
@@ -274,13 +281,13 @@ class GPT126MPP(TransformerLmSpmdPipelineAdam):
     transformer_layer_p.ln_tpl.reductions_in_fp32 = True
     transformer_layer_p.tr_fflayer_tpl.ln_tpl.reductions_in_fp32 = True
     task_p.model.lm_tpl.final_ln_tpl.reductions_in_fp32 = True
-    
+
     model_p.params_init = WeightInit.Gaussian(self.INIT_STD)
     softmax_init = WeightInit.Gaussian(self.SOFTMAX_INIT_STD)
     model_p.lm_tpl.softmax_tpl.params_init = softmax_init
-    
+
     model_p.apply_eval_sample_weights = True
-    
+
     ## set input, residual, attention dropout to DROPOUT_PROB, remaining dropout to 0
     stacked_p.dropout_prob = 0.0
     stacked_p.input_dropout_prob = self.DROPOUT_PROB
@@ -316,14 +323,14 @@ class LLaMA70BSyntheticSmall(BaseLLaMA, SyntheticDataset):
 if pp > 1:
   @experiment_registry.register
   class Synthetic126MCI(GPT126MPP, SyntheticDataset):
-    
+
     ICI_MESH_SHAPE = [pp, dp, fsdp, tp]
     DCN_MESH_SHAPE = [dcn_pp, dcn_dp, dcn_fsdp, 1]
     MICROBATCH_SIZE = 2
     NUM_STAGES = pp
     PERCORE_BATCH_SIZE = percore_batch_size
     FRPOP_DTYPE = dtype
-    
+
     def task(self):
       task_p = super().task()
       task_p.train.always_use_train_for_model_init=False
@@ -333,7 +340,7 @@ if pp > 1:
 else:
   @experiment_registry.register
   class Synthetic126MCI(Synthetic126M):
-    
+
     ICI_MESH_SHAPE = [dp, fsdp, tp]
     DCN_MESH_SHAPE = [dcn_dp, dcn_fsdp, 1]
     PERCORE_BATCH_SIZE = percore_batch_size
@@ -343,7 +350,7 @@ else:
 
     ## disable eval
     EVAL_INTERVAL_STEPS = 100000
-    
+
     def task(self):
       task_p = super().task()
 
@@ -374,6 +381,10 @@ export ENABLE_TE=$ENABLE_TE
 export NVTE_FUSED_ATTN=$NVTE_FUSED_ATTN
 export VOCAB_PATH=${VOCAB_PATH:-gs://t5-data/vocabs/cc_all.32000.100extra/sentencepiece.model}
 
+if [[ ${ENABLE_CUDNN_FA} -ne 0 ]]; then
+  ADDITIONAL_ARGS="${ADDITIONAL_ARGS} --fdl.USE_CUDNN_FLASH_ATTENTION=True"
+fi
+
 if [[ ${MODEL_TYPE} == "126M" ]]; then
   CONFIG=ci_configs.Synthetic126MCI
 elif [[ ${MODEL_TYPE} == "5B" ]]; then
diff --git a/.github/workflows/_ci.yaml b/.github/workflows/_ci.yaml
index fc04b83ab..426764323 100644
--- a/.github/workflows/_ci.yaml
+++ b/.github/workflows/_ci.yaml
@@ -11,6 +11,11 @@ on:
         description: 'Build date in YYYY-MM-DD format'
         required: false
         default: NOT SPECIFIED
+      CUDA_IMAGE:
+        type: string
+        description: CUDA image to use as base, e.g. nvidia/cuda:X.Y.Z-devel-ubuntu22.04
+        default: 'latest'
+        required: false
       MANIFEST_ARTIFACT_NAME:
         type: string
         description: 'Artifact name in current run w/ manifest/patches. Leaving empty uses manifest/patches in current branch'
@@ -37,6 +42,7 @@ jobs:
     uses: ./.github/workflows/_build_base.yaml
     with:
       ARCHITECTURE: ${{ inputs.ARCHITECTURE }}
+      BASE_IMAGE: ${{ inputs.CUDA_IMAGE }}
       BUILD_DATE: ${{ inputs.BUILD_DATE }}
       MANIFEST_ARTIFACT_NAME: ${{ inputs.MANIFEST_ARTIFACT_NAME }}
     secrets: inherit
diff --git a/.github/workflows/baselines/test_maxtext_metrics.py b/.github/workflows/baselines/test_maxtext_metrics.py
index bd180ecfe..a130c86c6 100644
--- a/.github/workflows/baselines/test_maxtext_metrics.py
+++ b/.github/workflows/baselines/test_maxtext_metrics.py
@@ -19,7 +19,7 @@
 def test_loss(baseline_filename):
     baseline_filepath = os.path.join(baselines_dir, baseline_filename)
     test_config = baseline_filename.split(".")[0]
-    event_file = os.path.join(results_dir, test_config, "logdir/tensorboard/events*")
+    event_file = os.path.join(results_dir, test_config, "logdir/tensorboard/logdir/events*")
     event_file = glob.glob(event_file)[0]
     with open(baseline_filepath, "r") as baseline_file:
         end_step = json.load(baseline_file)["end_step"]
@@ -31,7 +31,7 @@ def test_loss(baseline_filename):
 def test_step_time(baseline_filename):
     baseline_filepath = os.path.join(baselines_dir, baseline_filename)
     test_config = baseline_filename.split(".")[0]
-    event_file = os.path.join(results_dir, test_config, "logdir/tensorboard/events*")
+    event_file = os.path.join(results_dir, test_config, "logdir/tensorboard/logdir/events*")
     event_file = glob.glob(event_file)[0]
     with open(baseline_filepath, "r") as baseline_file:
         step_time_avg_expected = json.load(baseline_file)["step_time_avg"]
diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml
index 70aeff5ff..0c3c8bdb0 100644
--- a/.github/workflows/ci.yaml
+++ b/.github/workflows/ci.yaml
@@ -28,6 +28,11 @@ on:
         description: "(used if BUMP_MANIFEST=true) If true: attempt to PR/merge manifest branch"
         default: false
         required: false
+      CUDA_IMAGE:
+        type: string
+        description: CUDA image to use as base, e.g. nvidia/cuda:X.Y.Z-devel-ubuntu22.04
+        default: 'latest'
+        required: false
       SOURCE_OVERRIDES:
         type: string
         description: |
@@ -60,6 +65,7 @@ jobs:
       MANIFEST_ARTIFACT_NAME: ${{ steps.manifest-branch.outputs.MANIFEST_ARTIFACT_NAME }}
       MANIFEST_BRANCH: ${{ steps.manifest-branch.outputs.MANIFEST_BRANCH }}
       MERGE_BUMPED_MANIFEST: ${{ steps.manifest-branch.outputs.MERGE_BUMBED_MANIFEST }}
+      CUDA_IMAGE: ${{ steps.cuda-image.outputs.CUDA_IMAGE }}
     steps:
       - name: Cancel workflow run if the trigger is a draft PR
         id: cancel-if-draft
@@ -114,6 +120,17 @@ jobs:
             exit 1
           fi
       
+      - name: Determine CUDA image to use
+        id: cuda-image
+        shell: bash -x -e {0}
+        run: |
+          if [[ "${{ github.event_name }}" == "workflow_dispatch" ]]; then
+            CUDA_IMAGE="${{ inputs.CUDA_IMAGE }}"
+          else
+            CUDA_IMAGE="latest"
+          fi
+          echo "CUDA_IMAGE=${CUDA_IMAGE}" >> $GITHUB_OUTPUT
+
   bump-manifest:
     needs: metadata
     runs-on: ubuntu-22.04
@@ -177,6 +194,7 @@ jobs:
     with:
       ARCHITECTURE: amd64
       BUILD_DATE: ${{ needs.metadata.outputs.BUILD_DATE }}
+      CUDA_IMAGE: ${{ needs.metadata.outputs.CUDA_IMAGE }}
       MANIFEST_ARTIFACT_NAME: ${{ needs.metadata.outputs.MANIFEST_ARTIFACT_NAME }}
       SOURCE_URLREFS: ${{ needs.bump-manifest.outputs.SOURCE_URLREFS }}
     secrets: inherit
@@ -187,6 +205,7 @@ jobs:
     with:
       ARCHITECTURE: arm64
       BUILD_DATE: ${{ needs.metadata.outputs.BUILD_DATE }}
+      CUDA_IMAGE: ${{ needs.metadata.outputs.CUDA_IMAGE }}
       MANIFEST_ARTIFACT_NAME: ${{ needs.metadata.outputs.MANIFEST_ARTIFACT_NAME }}
       SOURCE_URLREFS: ${{ needs.bump-manifest.outputs.SOURCE_URLREFS }}
     secrets: inherit
diff --git a/README.md b/README.md
index 66d9b2a4e..1764c5f00 100644
--- a/README.md
+++ b/README.md
@@ -300,6 +300,8 @@ The [JAX image](https://github.com/NVIDIA/JAX-Toolbox/pkgs/container/jax) is emb
 
 There are various other XLA flags users can set to improve performance. For a detailed explanation of these flags, please refer to the [GPU performance](./rosetta/docs/GPU_performance.md) doc. XLA flags can be tuned per workflow. For example, each script in [contrib/gpu/scripts_gpu](https://github.com/google/paxml/tree/main/paxml/contrib/gpu/scripts_gpu) sets its own [XLA flags](https://github.com/google/paxml/blob/93fbc8010dca95af59ab615c366d912136b7429c/paxml/contrib/gpu/scripts_gpu/benchmark_gpt_multinode.sh#L30-L33).
 
+For a list of previously used XLA flags that are no longer needed, please also refer to the [GPU performance](./rosetta/docs/GPU_performance.md#previously-used-xla-flags) page.
+
 ## Profiling JAX programs on GPU
 See [this page](./docs/profiling.md) for more information about how to profile JAX programs on GPU.
 
diff --git a/rosetta/docs/GPU_performance.md b/rosetta/docs/GPU_performance.md
index c5456e3c4..fabbc6963 100644
--- a/rosetta/docs/GPU_performance.md
+++ b/rosetta/docs/GPU_performance.md
@@ -128,6 +128,10 @@ Fine-grain control to improve performance by initializing a NCCL communicator to
 - --xla_gpu_enable_cudnn_fmha=false (enables XLA pattern matcher to detect multi-headed attention pattern in JAX)
 - --xla_disable_hlo_passes=<> (turns off specific HLO passes; can be used for debugging)
 
+## Previously used XLA Flags
 
-
+The following flags were used previously used but no longer required.
+- --xla_gpu_enable_async_reduce_scatter, --xla_gpu_enable_async_all_reduce, --xla_gpu_enable_async_all_gather ; Turned on by default, no longer needed
+- --xla_gpu_enable_highest_priority_async_stream ; Turned on by default
+- --xla_gpu_enable_triton_softmax_fusion ; Deprecated, no longer used
 
diff --git a/rosetta/docs/NATIVE_FP8.md b/rosetta/docs/NATIVE_FP8.md
index dd3aa1bae..069b06fdd 100644
--- a/rosetta/docs/NATIVE_FP8.md
+++ b/rosetta/docs/NATIVE_FP8.md
@@ -111,13 +111,11 @@ Enabling this feature is effortless. Users only need to include the option `--fd
 In addition to the suggested XLA flags mentioned in [this section](https://github.com/NVIDIA/JAX-Toolbox/blob/main/rosetta/rosetta/projects/pax/README.md#xla-flags), we also recommend setting these following XLA flags. The execution script should look like:
 ```bash
 export XLA_FLAGS=" \
-    --xla_gpu_enable_reduction_epilogue_fusion=false \
     --xla_gpu_enable_triton_gemm=false \
-    --xla_gpu_enable_cudnn_fmha=false \
-    --xla_gpu_enable_cudnn_layer_norm=true \
-    --xla_gpu_enable_cublaslt=true \
-    --xla_gpu_enable_latency_hiding_scheduler=true \
-    --xla_gpu_all_reduce_combine_threshold_bytes=51200 "
+    --xla_gpu_enable_pipelined_all_reduce=false \
+    --xla_gpu_enable_pipelined_all_gather=false \
+    --xla_gpu_enable_pipelined_reduce_scatter=false \
+"
 export ENABLE_TE=0
 python -m paxml.main \
     ...
@@ -125,8 +123,7 @@ python -m paxml.main \
     ...
 ```
 
-Please ensure you include the first two flags, `--xla_gpu_enable_reduction_epilogue_fusion=false` and `--xla_gpu_enable_triton_gemm=false`, as they are essential for enabling the FP8 functionality. The additional flags primarily focus on performance enhancement and should also prove beneficial for non-FP8 executions.
-
+Please not that disabling the triton gemm and pipelined collectives is essential for enabling the FP8 functionality and performance.
 
 ## Transformer Engine vs Native FP8 Support
 Native XLA-FP8 specifically targets matrix multiplication operations. In contrast, the Transformer Engine focuses on enhancing the overall performance of the entire transformer layer. This encompasses not only the FP8 matrix multiplication but also attention mechanisms, layer normalizations, and other components.
diff --git a/rosetta/docs/PGLE.md b/rosetta/docs/PGLE.md
index 02e5f5294..2425ddffe 100644
--- a/rosetta/docs/PGLE.md
+++ b/rosetta/docs/PGLE.md
@@ -70,7 +70,6 @@ export XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true
 --xla_gpu_enable_pipelined_reduce_scatter=true
 --xla_gpu_enable_pipelined_all_reduce=true
 --xla_gpu_enable_while_loop_double_buffering=true
---xla_gpu_enable_triton_softmax_fusion=false
 --xla_gpu_enable_all_gather_combine_by_dim=false
 --xla_gpu_enable_reduce_scatter_combine_by_dim=false
 --xla_disable_hlo_passes=rematerialization
diff --git a/rosetta/rosetta/projects/maxtext/README.md b/rosetta/rosetta/projects/maxtext/README.md
index fde5a9125..2320a7ed9 100644
--- a/rosetta/rosetta/projects/maxtext/README.md
+++ b/rosetta/rosetta/projects/maxtext/README.md
@@ -67,12 +67,9 @@ In order to obtain the best performance, please set the appropriate XLA flags. W
 The [GPU Performance document](../../../docs/GPU_performance.md) provides a detailed description of the XLA flags that can be set to optimize performance. These are the recommended XLA flags to get good performance for MaxText.
 
 ```
-XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true 
-            --xla_gpu_enable_async_all_gather=true 
-            --xla_gpu_enable_async_reduce_scatter=true 
+XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true
             --xla_gpu_enable_triton_gemm=false
-            --xla_gpu_graph_level=0 
-            --xla_gpu_enable_async_all_reduce=true 
+            --xla_gpu_graph_level=0
             --xla_gpu_all_reduce_combine_threshold_bytes=1073741824 
             --xla_gpu_all_gather_combine_threshold_bytes=1073741824 
             --xla_gpu_reduce_scatter_combine_threshold_bytes=134217728
@@ -80,7 +77,6 @@ XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true
             --xla_gpu_enable_pipelined_reduce_scatter=true 
             --xla_gpu_enable_pipelined_all_reduce=true 
             --xla_gpu_enable_while_loop_double_buffering=true
-            --xla_gpu_enable_triton_softmax_fusion=false 
             --xla_gpu_enable_all_gather_combine_by_dim=false 
             --xla_gpu_enable_reduce_scatter_combine_by_dim=false 
             --xla_disable_hlo_passes=rematerialization"
diff --git a/rosetta/rosetta/projects/maxtext/scripts/example_slurm.sub b/rosetta/rosetta/projects/maxtext/scripts/example_slurm.sub
index e96eaa781..0ca3fd802 100644
--- a/rosetta/rosetta/projects/maxtext/scripts/example_slurm.sub
+++ b/rosetta/rosetta/projects/maxtext/scripts/example_slurm.sub
@@ -53,11 +53,8 @@ export NCCL_IB_SL=1
 
 # Set XLA Flags
 export XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true
-                --xla_gpu_enable_async_all_gather=true
-                --xla_gpu_enable_async_reduce_scatter=true
                 --xla_gpu_enable_triton_gemm=false
                 --xla_gpu_graph_level=0
-                --xla_gpu_enable_async_all_reduce=true
                 --xla_gpu_all_reduce_combine_threshold_bytes=1073741824
                 --xla_gpu_all_gather_combine_threshold_bytes=1073741824
                 --xla_gpu_reduce_scatter_combine_threshold_bytes=134217728
@@ -65,12 +62,9 @@ export XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true
                 --xla_gpu_enable_pipelined_reduce_scatter=true
                 --xla_gpu_enable_pipelined_all_reduce=true
                 --xla_gpu_enable_while_loop_double_buffering=true
-                --xla_gpu_enable_triton_softmax_fusion=false
                 --xla_gpu_enable_all_gather_combine_by_dim=false
                 --xla_gpu_enable_reduce_scatter_combine_by_dim=false
-                --xla_disable_hlo_passes=rematerialization
-                --xla_gpu_enable_custom_fusions=false
-                --xla_gpu_enable_address_computation_fusion=false"
+                --xla_disable_hlo_passes=rematerialization"
 
 # Make directories that may not exist
 mkdir -p $BASE_WORKSPACE_DIR
diff --git a/rosetta/rosetta/projects/maxtext/xla_flags/llama2-7b-1N8G.env b/rosetta/rosetta/projects/maxtext/xla_flags/llama2-7b-1N8G.env
new file mode 100644
index 000000000..d999f5b5e
--- /dev/null
+++ b/rosetta/rosetta/projects/maxtext/xla_flags/llama2-7b-1N8G.env
@@ -0,0 +1,24 @@
+set -x
+NUM_NODES=1
+NUM_GPUS=8
+THRESHOLD_BYTES=1073741824
+export XLA_FLAGS="\
+    --xla_gpu_enable_latency_hiding_scheduler=true \
+    --xla_gpu_enable_triton_gemm=false \
+    --xla_gpu_graph_level=0 \
+    --xla_gpu_enable_highest_priority_async_stream=true \
+    --xla_gpu_all_reduce_combine_threshold_bytes=${THRESHOLD_BYTES} \
+    --xla_gpu_all_gather_combine_threshold_bytes=$((THRESHOLD_BYTES/(NUM_NODES*NUM_GPUS))) \
+    --xla_gpu_reduce_scatter_combine_threshold_bytes=$((THRESHOLD_BYTES/(NUM_NODES*NUM_GPUS*2))) \
+    --xla_gpu_enable_pipelined_all_gather=true \
+    --xla_gpu_enable_pipelined_reduce_scatter=true \
+    --xla_gpu_enable_pipelined_all_reduce=true \
+    --xla_gpu_enable_while_loop_double_buffering=true \
+    --xla_gpu_enable_triton_softmax_fusion=false \
+    --xla_gpu_enable_all_gather_combine_by_dim=false \
+    --xla_gpu_enable_reduce_scatter_combine_by_dim=false \
+    --xla_disable_hlo_passes=rematerialization \
+    "
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.9
+unset NUM_NODES NUM_GPUS THRESHOLD_BYTES
+set +x
diff --git a/rosetta/rosetta/projects/pax/README.md b/rosetta/rosetta/projects/pax/README.md
index 6ac4dc150..d1829b847 100644
--- a/rosetta/rosetta/projects/pax/README.md
+++ b/rosetta/rosetta/projects/pax/README.md
@@ -138,10 +138,10 @@ The [GPU Performance document](../../../docs/GPU_performance.md) provides a deta
 For the the 126M model, we recommend setting `--xla_gpu_all_reduce_combine_threshold_bytes=33554432`, which is different from the value recommended in `paxml/contrib/gpu/scripts_gpu/run_pile_multinode.sh`. To overwrite the default XLA flags set in the script, set the `BASE_XLA_FLAGS` environment variable prior to running `run_pile_multinode` as follows:
 
 ```
-BASE_XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true --xla_gpu_enable_triton_gemm=false
-                --xla_gpu_enable_async_all_gather=true --xla_gpu_enable_async_reduce_scatter=true
-                --xla_gpu_enable_triton_softmax_fusion=false  --xla_gpu_all_reduce_combine_threshold_bytes=33554432
-                --xla_gpu_graph_level=0 --xla_gpu_enable_async_all_reduce=true" bash run_pile_multinode.sh ...
+BASE_XLA_FLAGS="--xla_gpu_enable_latency_hiding_scheduler=true
+                --xla_gpu_enable_triton_gemm=false
+                --xla_gpu_all_reduce_combine_threshold_bytes=33554432
+                --xla_gpu_graph_level=0" bash run_pile_multinode.sh ...
 ```
 
 # Configs
diff --git a/rosetta/rosetta/projects/pax/xla_flags/common.env b/rosetta/rosetta/projects/pax/xla_flags/common.env
new file mode 100644
index 000000000..26c819143
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/common.env
@@ -0,0 +1,13 @@
+set -x
+THRESHOLD_BYTES=51200
+export XLA_FLAGS="\
+    --xla_gpu_enable_latency_hiding_scheduler=true \
+    --xla_allow_excess_precision \
+    --xla_gpu_enable_highest_priority_async_stream=true \
+    --xla_gpu_enable_triton_softmax_fusion=false \
+    --xla_gpu_all_reduce_combine_threshold_bytes=${THRESHOLD_BYTES} \
+    --xla_gpu_graph_level=0 \
+    "
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.8
+unset THRESHOLD_BYTES
+set +x
diff --git a/rosetta/rosetta/projects/pax/xla_flags/glam-126m64e.env b/rosetta/rosetta/projects/pax/xla_flags/glam-126m64e.env
new file mode 100644
index 000000000..8b0237170
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/glam-126m64e.env
@@ -0,0 +1,3 @@
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source $SCRIPT_DIR/common.env
+unset SCRIPT_DIR
diff --git a/rosetta/rosetta/projects/pax/xla_flags/glam-64b64e.env b/rosetta/rosetta/projects/pax/xla_flags/glam-64b64e.env
new file mode 100644
index 000000000..8b0237170
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/glam-64b64e.env
@@ -0,0 +1,3 @@
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source $SCRIPT_DIR/common.env
+unset SCRIPT_DIR
diff --git a/rosetta/rosetta/projects/pax/xla_flags/gpt-126m.env b/rosetta/rosetta/projects/pax/xla_flags/gpt-126m.env
new file mode 100644
index 000000000..e5b97b466
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/gpt-126m.env
@@ -0,0 +1,14 @@
+set -x
+THRESHOLD_BYTES=33554432
+export XLA_FLAGS="\
+    --xla_gpu_enable_latency_hiding_scheduler=true \
+    --xla_allow_excess_precision \
+    --xla_gpu_enable_highest_priority_async_stream=true \
+    --xla_gpu_enable_triton_softmax_fusion=false \
+    --xla_gpu_all_reduce_combine_threshold_bytes=${THRESHOLD_BYTES} \
+    --xla_gpu_graph_level=0 \
+    --xla_gpu_enable_cudnn_fmha=false \
+    "
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.8
+unset THRESHOLD_BYTES
+set +x
diff --git a/rosetta/rosetta/projects/pax/xla_flags/gpt-175b.env b/rosetta/rosetta/projects/pax/xla_flags/gpt-175b.env
new file mode 100644
index 000000000..8b0237170
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/gpt-175b.env
@@ -0,0 +1,3 @@
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source $SCRIPT_DIR/common.env
+unset SCRIPT_DIR
diff --git a/rosetta/rosetta/projects/pax/xla_flags/gpt-5b.env b/rosetta/rosetta/projects/pax/xla_flags/gpt-5b.env
new file mode 100644
index 000000000..8b0237170
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/gpt-5b.env
@@ -0,0 +1,3 @@
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source $SCRIPT_DIR/common.env
+unset SCRIPT_DIR
diff --git a/rosetta/rosetta/projects/pax/xla_flags/grok-proxy.env b/rosetta/rosetta/projects/pax/xla_flags/grok-proxy.env
new file mode 100644
index 000000000..e48b76dcf
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/grok-proxy.env
@@ -0,0 +1,25 @@
+set -x
+ALL_REDUCE_THRESHOLD_BYTES=3221225472
+ALL_GATHER_THRESHOLD_BYTES=3221225472
+REDUCE_SCATTER_THRESHOLD_BYTES=402653184
+export XLA_FLAGS="\
+    --xla_gpu_enable_latency_hiding_scheduler=true \
+    --xla_allow_excess_precision \
+    --xla_gpu_enable_highest_priority_async_stream=true \
+    --xla_gpu_enable_triton_softmax_fusion=false \
+    --xla_gpu_all_reduce_combine_threshold_bytes=${ALL_REDUCE_THRESHOLD_BYTES} \
+    --xla_gpu_graph_level=0 \
+    --xla_gpu_all_gather_combine_threshold_bytes=${ALL_GATHER_THRESHOLD_BYTES} \
+    --xla_gpu_reduce_scatter_combine_threshold_bytes=${REDUCE_SCATTER_THRESHOLD_BYTES} \
+    --xla_gpu_enable_pipelined_all_gather=true \
+    --xla_gpu_enable_pipelined_reduce_scatter=true \
+    --xla_gpu_enable_pipelined_all_reduce=true \
+    --xla_gpu_enable_while_loop_double_buffering=true \
+    --xla_gpu_enable_all_gather_combine_by_dim=false \
+    --xla_gpu_enable_reduce_scatter_combine_by_dim=false \
+    --xla_disable_hlo_passes=rematerialization \
+    --xla_gpu_enable_custom_fusions=true
+    "
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.9
+unset ALL_REDUCE_THRESHOLD_BYTES ALL_GATHER_THRESHOLD_BYTES REDUCE_SCATTER_THRESHOLD_BYTES
+set +x
diff --git a/rosetta/rosetta/projects/pax/xla_flags/llama-70b.env b/rosetta/rosetta/projects/pax/xla_flags/llama-70b.env
new file mode 100644
index 000000000..8b0237170
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/llama-70b.env
@@ -0,0 +1,3 @@
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source $SCRIPT_DIR/common.env
+unset SCRIPT_DIR
diff --git a/rosetta/rosetta/projects/pax/xla_flags/llama-7b-lora.env b/rosetta/rosetta/projects/pax/xla_flags/llama-7b-lora.env
new file mode 100644
index 000000000..d1568e92c
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/llama-7b-lora.env
@@ -0,0 +1,4 @@
+set -x
+echo "$0 uses default XLA_FLAGS='${XLA_FLAGS:-}'"
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.85
+set +x
diff --git a/rosetta/rosetta/projects/pax/xla_flags/llama-7b.env b/rosetta/rosetta/projects/pax/xla_flags/llama-7b.env
new file mode 100644
index 000000000..bd4ae50d5
--- /dev/null
+++ b/rosetta/rosetta/projects/pax/xla_flags/llama-7b.env
@@ -0,0 +1,4 @@
+set -x
+echo "$0 uses default XLA_FLAGS='${XLA_FLAGS:-}'"
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.8
+set +x
diff --git a/rosetta/rosetta/projects/t5x/xla_flags/t5.env b/rosetta/rosetta/projects/t5x/xla_flags/t5.env
new file mode 100644
index 000000000..bd4ae50d5
--- /dev/null
+++ b/rosetta/rosetta/projects/t5x/xla_flags/t5.env
@@ -0,0 +1,4 @@
+set -x
+echo "$0 uses default XLA_FLAGS='${XLA_FLAGS:-}'"
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.8
+set +x
diff --git a/rosetta/rosetta/projects/vit/xla_flags/vit-base-highgbs.env b/rosetta/rosetta/projects/vit/xla_flags/vit-base-highgbs.env
new file mode 100644
index 000000000..45140ed88
--- /dev/null
+++ b/rosetta/rosetta/projects/vit/xla_flags/vit-base-highgbs.env
@@ -0,0 +1,4 @@
+set -x
+echo "$0 uses default XLA_FLAGS='${XLA_FLAGS:-}'"
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.75
+set +x
diff --git a/rosetta/rosetta/projects/vit/xla_flags/vit-base.env b/rosetta/rosetta/projects/vit/xla_flags/vit-base.env
new file mode 100644
index 000000000..882c9e9e8
--- /dev/null
+++ b/rosetta/rosetta/projects/vit/xla_flags/vit-base.env
@@ -0,0 +1,4 @@
+set -x
+echo "$0 uses default XLA_FLAGS='${XLA_FLAGS:-}'"
+export XLA_PYTHON_CLIENT_MEM_FRACTION=0.9
+set +x