diff --git a/SUPPORTED_OPS.md b/SUPPORTED_OPS.md
index 43f087f..404c776 100644
--- a/SUPPORTED_OPS.md
+++ b/SUPPORTED_OPS.md
@@ -19,7 +19,7 @@
 # Supported Ops
 
 This file was automatically generated by Vela using the `--supported-ops-report` parameter.  
-Vela version: `3.11.0`
+Vela version: `3.12.0`
 
 This file complies with
 [**Gitiles Markdown syntax**](https://gerrit.googlesource.com/gitiles/+/HEAD/Documentation/markdown.md)
@@ -408,7 +408,7 @@
 - ellipsis_mask must be 0
 - new_axis_mask and shrink_axis_mask cannot both be set
 - Slice 'end' values must be greater than 'begin' values
-- All Strides values must be 1
+- Batch and channel stride values must be 1
 - Offset attribute must be False
 
 ### TFLite SUB Constraints
diff --git a/ethosu/vela/high_level_command_to_npu_op.py b/ethosu/vela/high_level_command_to_npu_op.py
index 52d0718..71181d0 100644
--- a/ethosu/vela/high_level_command_to_npu_op.py
+++ b/ethosu/vela/high_level_command_to_npu_op.py
@@ -410,16 +410,20 @@
 
     assert strides is not None
 
+    multiplied_strides = strides.copy()
     if stride_multiplier and stride_multiplier != [1, 1, 1]:
         assert (
             tens.format == TensorFormat.NHWC
         ), "Only default stride multiplier ([1, 1, 1]) supported for NHCWB16 format"
         # Multiply strides for C/H/W (in that order) with corresponding stride factor
         for i, stride_factor in enumerate(stride_multiplier, start=1):
-            strides[i] *= stride_factor
+            multiplied_strides[i] *= stride_factor
+
+    # Stride multiplier only affects tiles and addresses for OFM
+    _strides = multiplied_strides if is_ofm else strides
 
     height_0, height_1, width_0, addresses = tens.addresses_for_rolling_buffer(
-        box.start_coord, box.end_coord, strides, op_shape4D
+        box.start_coord, box.end_coord, _strides, op_shape4D
     )
 
     for idx, offset in enumerate(tile_base_offsets):
@@ -427,7 +431,9 @@
     fm.tiles = NpuTileBox(
         height_0=height_0, height_1=height_1, width_0=width_0, addresses=[int(addr) for addr in addresses]
     )
-    fm.strides = NpuShape3D(height=int(strides[2]), width=int(strides[3]), depth=int(strides[1]))
+    fm.strides = NpuShape3D(
+        height=int(multiplied_strides[2]), width=int(multiplied_strides[3]), depth=int(multiplied_strides[1])
+    )
     fm.name = tens.name
     return fm
 
@@ -518,8 +524,9 @@
     ifm_height = cmd.ifm_box.get_block().height
     ifm_width = cmd.ifm_box.get_block().width
     ifm_depth = get_ifm_depth(op.type.npu_block_type, cmd.ifm_box, cmd.ofm_box)
-
-    npu_op.ifm = create_feature_map(cmd.ifm_tensor, cmd.ifm_box, arch, ps.ifm_shapes[0], op.tile_base_offsets_ifm[0])
+    npu_op.ifm = create_feature_map(
+        cmd.ifm_tensor, cmd.ifm_box, arch, ps.ifm_shapes[0], op.tile_base_offsets_ifm[0], op.ifm_stride_multiplier[0]
+    )
     npu_op.ifm.shape = NpuShape3D(height=ifm_height, width=ifm_width, depth=ifm_depth)
     npu_op.ifm.quantization = get_ifm_or_ifm2_quantization(ps, cmd.ifm_tensor)
 
diff --git a/ethosu/vela/operation.py b/ethosu/vela/operation.py
index a831537..9a917f2 100644
--- a/ethosu/vela/operation.py
+++ b/ethosu/vela/operation.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
+# SPDX-FileCopyrightText: Copyright 2020-2024 Arm Limited and/or its affiliates <open-source-office@arm.com>
 #
 # SPDX-License-Identifier: Apache-2.0
 #
@@ -511,6 +511,7 @@
         "tile_base_offsets_ifm",
         "tile_base_offsets_ofm",
         "ofm_stride_multiplier",
+        "ifm_stride_multiplier",
     )
 
     def __init__(self, op_type: Op, name: str):
@@ -554,8 +555,9 @@
         self.tile_base_offsets_ifm: List[List[int]] = [[0, 0, 0, 0], [0, 0, 0, 0]]
         # ofm (nhwc)
         self.tile_base_offsets_ofm: List[int] = [0, 0, 0, 0]
-        # For interleaved/sparse outputs - stride is multiplied with the stride factor of the corresponding axis
-        # Order is [C, H, W] - default is no multiplication
+        # Stride is multiplied with the ifm/ofm stride factor of the corresponding axis
+        # Order is [C, H, W]
+        self.ifm_stride_multiplier: List[List[int]] = [[1, 1, 1], [1, 1, 1]]
         self.ofm_stride_multiplier: List[int] = [1, 1, 1]
 
     def clone(self, suffix="_clone"):
@@ -585,6 +587,7 @@
         res.ifm_resampling_mode = self.ifm_resampling_mode
         res.tile_base_offsets_ifm = [_ifm.copy() for _ifm in self.tile_base_offsets_ifm]
         res.tile_base_offsets_ofm = self.tile_base_offsets_ofm.copy()
+        res.ifm_stride_multiplier = [_ifm.copy() for _ifm in self.ifm_stride_multiplier]
         res.ofm_stride_multiplier = self.ofm_stride_multiplier.copy()
 
         return res
@@ -763,6 +766,7 @@
         offset_start = None
         offset_end = None
         axis = None
+        strides_tens = None
         if self.type == Op.Split:
             num_splits = self.attrs.get("num_splits")
             axis_tens = self.inputs[0]
@@ -831,7 +835,7 @@
         else:
             assert False
 
-        return input_tens, outputs, axis, offset_start, offset_end
+        return input_tens, outputs, axis, offset_start, offset_end, strides_tens
 
     def set_activation_lut(self, lut_tensor):
         self.activation = ActivationFunction(Op.LUT)
diff --git a/ethosu/vela/test/test_tflite_supported_operators.py b/ethosu/vela/test/test_tflite_supported_operators.py
index e65717a..3b15b31 100644
--- a/ethosu/vela/test/test_tflite_supported_operators.py
+++ b/ethosu/vela/test/test_tflite_supported_operators.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
+# SPDX-FileCopyrightText: Copyright 2020-2024 Arm Limited and/or its affiliates <open-source-office@arm.com>
 #
 # SPDX-License-Identifier: Apache-2.0
 #
@@ -542,7 +542,9 @@
 def test_constraint_stridedslice_stride_values():
     # Unsupported strides
     op = create_strided_slice()
-    op.inputs[3].values = [1, 1, 2, 1]
+    op.inputs[3].values = [1, 2, 2, 1]
+    assert support.is_operator_supported(op)
+    op.inputs[3].values = [2, 1, 1, 1]
     assert not support.is_operator_supported(op)
 
 
diff --git a/ethosu/vela/tflite_graph_optimiser.py b/ethosu/vela/tflite_graph_optimiser.py
index 3af8588..ccbb1f2 100644
--- a/ethosu/vela/tflite_graph_optimiser.py
+++ b/ethosu/vela/tflite_graph_optimiser.py
@@ -141,7 +141,7 @@
         if not split_op.run_on_npu:
             return tens
 
-        inp, outputs, axis, offset_start, offset_end = split_op.get_split_inputs_axis()
+        inp, outputs, axis, offset_start, offset_end, strides_tens = split_op.get_split_inputs_axis()
 
         tens.ops = []
         new_op = Operation(Op.SplitSliceRead, split_op.name)
@@ -150,8 +150,10 @@
         if None in (offset_end, offset_start):
             read_shape = None
         else:
-            # the read shape is relative to each start offset
-            read_shape = Shape4D([oe - os for oe, os in zip(offset_end, offset_start)])
+            # The read shape is relative to each start offset
+            # Limit read shape to the size of the IFM - offset is not necessarily limited
+            ifm_dims = split_op.ifm_shapes[0].as_list()
+            read_shape = Shape4D([min(oe, ifm_dim) - os for oe, os, ifm_dim in zip(offset_end, offset_start, ifm_dims)])
 
         # For Split the offset cannot be extracted from the tensor so it has to
         # be calculated from the index of the output tensor
@@ -182,6 +184,9 @@
         new_op.set_output_tensor(tens)
         new_op.ifm_shapes.append(Shape4D(inp.shape))
         new_op.ofm_shapes.append(split_op.ofm_shapes[ofm_shape_idx])
+        # Set stride multiplier in H/W if a stride tensor is provided
+        s_h, s_w = (strides_tens.values[-3], strides_tens.values[-2]) if strides_tens else (1, 1)
+        new_op.ifm_stride_multiplier[0] = [1, s_h, s_w]  # C/H/W
         DebugDatabase.add_optimised(split_op, new_op)
 
     return tens
@@ -193,18 +198,24 @@
         # Check if it is possible to put the SplitSliceRead on the tensor consumer(s),
         # or if an avgpool need to be inserted
         # Not possible to move:
+        #   - if ifm stride multiplier is larger than one in any dimension
         #   - if consumer is a Transpose op since ifm shape has been reshaped and can not be changed
         #   - if consumer is elementwise and ifm needs to be broadcasted
-        if op.ofm_shapes[0] == Shape4D.from_list(op.ofm.shape) and all(
-            consumer is not None
-            and consumer.run_on_npu
-            and consumer.type not in memory_only_ops
-            and consumer.original_type != Op.Transpose
-            and check_splitsliceread_to_consumer_shape(op, consumer)
-            and not (
-                consumer.type.is_binary_elementwise_op() and Shape4D.from_list(consumer.ofm.shape) != op.ofm_shapes[0]
+        if (
+            op.ofm_shapes[0] == Shape4D.from_list(op.ofm.shape)
+            and all(s_mul == 1 for s_mul in op.ifm_stride_multiplier[0])
+            and all(
+                consumer is not None
+                and consumer.run_on_npu
+                and consumer.type not in memory_only_ops
+                and consumer.original_type != Op.Transpose
+                and check_splitsliceread_to_consumer_shape(op, consumer)
+                and not (
+                    consumer.type.is_binary_elementwise_op()
+                    and Shape4D.from_list(consumer.ofm.shape) != op.ofm_shapes[0]
+                )
+                for consumer in op.ofm.consumer_list
             )
-            for consumer in op.ofm.consumer_list
         ):
             # SplitSliceRead can be performed by tensor consumer(s)
             for cons_op in list(op.ofm.consumer_list):
@@ -219,6 +230,9 @@
             avgpool_op.ofm_shapes.append(op.ofm_shapes[0])
             avgpool_op.read_offsets[0] = op.read_offsets[0]
             avgpool_op.read_shapes[0] = op.read_shapes[0]
+            if any(s_mul != 1 for s_mul in op.ifm_stride_multiplier[0]):
+                avgpool_op.ifm_stride_multiplier[0] = op.ifm_stride_multiplier[0].copy()
+                avgpool_op.ifm.force_linear_format = True
 
             op.ifm.consumer_list.remove(op)
             DebugDatabase.add_optimised(op, avgpool_op)
diff --git a/ethosu/vela/tflite_supported_operators.py b/ethosu/vela/tflite_supported_operators.py
index 91a3ee8..b293a2e 100644
--- a/ethosu/vela/tflite_supported_operators.py
+++ b/ethosu/vela/tflite_supported_operators.py
@@ -841,10 +841,11 @@
 
     @staticmethod
     def constraint_stridedslice_stride_values(op):
-        "All Strides values must be 1"
+        "Batch and channel stride values must be 1"
         strides = op.inputs[3]
-        valid = all(stride == 1 for stride in strides.values)
-        return valid, f"Op has strides values {strides.values}"
+        s_c = strides.values[-1]
+        s_n = strides.values[0] if len(strides.values) > 3 else 1
+        return s_n == s_c == 1, f"Op has strides values {strides.values}"
 
     @staticmethod
     def constraint_stridedslice_offset_false(op):