diff --git a/backends/arm/scripts/docgen/generate_op_support.py b/backends/arm/scripts/docgen/generate_op_support.py
index 33c85007dee..75d71e64230 100644
--- a/backends/arm/scripts/docgen/generate_op_support.py
+++ b/backends/arm/scripts/docgen/generate_op_support.py
@@ -11,6 +11,7 @@
 Examples:
     python backends/arm/scripts/docgen/generate_op_support.py --backend vgf
     python backends/arm/scripts/docgen/generate_op_support.py --backend u55
+    python backends/arm/scripts/docgen/generate_op_support.py --backend u85
     python backends/arm/scripts/docgen/generate_op_support.py --backend u55 --debug --html
     python backends/arm/scripts/docgen/generate_op_support.py --backend vgf --check --strict-ast
 
@@ -104,6 +105,22 @@ class BackendConfig:
         filter_u55_unsupported_ops=True,
         max_missing_profile_cells=4,
     ),
+    "u85": BackendConfig(
+        key="u85",
+        name="Ethos-U85",
+        pipeline_class_names=frozenset({"EthosU85PipelineINT"}),
+        pipeline_label="EthosU85PipelineINT",
+        tosa_spec="TOSA-1.0+INT+int16+int4+cf",
+        default_output=Path("docs/source/backends/arm-ethos-u/U85_op_support.md"),
+        quantize_keyword=None,
+        quantize_default=True,
+        default_profile="INT",
+        support_profile_order=("INT",),
+        # A missing Corstone-320 FVP is infrastructure, not evidence that the
+        # operator itself is unsupported.
+        infrastructure_xfail_markers=frozenset({"XfailIfNoCorstone320"}),
+        max_missing_profile_cells=10,
+    ),
 }
 
 # Compatibility globals used by the mature scanner implementation. They are
@@ -418,6 +435,25 @@ def _activate_backend(backend: str | BackendConfig) -> BackendConfig:
     },
 }
 
+# Existing U85 runtime tests below intentionally suppress direct ATen/Edge
+# assertions because quantization/decomposition changes the graph. They still
+# provide positive runtime coverage for the exported operator.
+U85_EXPLICIT_BACKEND_COVERAGE: dict[tuple[str, str], dict[str, set[str]]] = {
+    (
+        "backends/arm/test/ops/test_div_tensor_mode.py",
+        "test_div_tensor_mode_u85_INT",
+    ): {
+        "INT": {"torch.ops.aten.div.Tensor_mode"},
+    },
+    (
+        "backends/arm/test/ops/test_silu.py",
+        "test_silu_u85_INT",
+    ): {
+        "INT": {"torch.ops.aten.silu.default"},
+    },
+}
+
+
 # These exported operators pass a generic TOSA positive-support declaration,
 # but their actual U55 lowering path reaches an unsupported operation or a
 # restriction that cannot support the general exported operator. Keep these
@@ -438,6 +474,8 @@ def _active_explicit_backend_coverage() -> dict[tuple[str, str], dict[str, set[s
         return VGF_EXPLICIT_BACKEND_COVERAGE
     if ACTIVE_BACKEND_KEY == "u55":
         return U55_EXPLICIT_BACKEND_COVERAGE
+    if ACTIVE_BACKEND_KEY == "u85":
+        return U85_EXPLICIT_BACKEND_COVERAGE
     return {}
 
 
@@ -2369,6 +2407,9 @@ def _collect_backend_custom_partition_ops(
     to the profiles for which they are actually registered.
 
     """
+    if ACTIVE_BACKEND_KEY != "vgf":
+        return {}
+
     from executorch.backends.arm.vgf import VgfCompileSpec, VgfPartitioner
 
     enabled_profiles = {
diff --git a/backends/arm/scripts/pre-push b/backends/arm/scripts/pre-push
index 96284645402..6fa37b35a2d 100755
--- a/backends/arm/scripts/pre-push
+++ b/backends/arm/scripts/pre-push
@@ -35,6 +35,7 @@ DOCGEN_OUTPUTS=(
 OP_SUPPORT_SCRIPT="backends/arm/scripts/docgen/generate_op_support.py"
 VGF_OP_SUPPORT_OUTPUT="docs/source/backends/arm-vgf/VGF_op_support.md"
 U55_OP_SUPPORT_OUTPUT="docs/source/backends/arm-ethos-u/U55_op_support.md"
+U85_OP_SUPPORT_OUTPUT="docs/source/backends/arm-ethos-u/U85_op_support.md"
 
 RUN_DOCGEN=0
 
@@ -353,6 +354,7 @@ fi
 
 run_op_support_checks "vgf" "VGF" "$VGF_OP_SUPPORT_OUTPUT"
 run_op_support_checks "u55" "Ethos-U55" "$U55_OP_SUPPORT_OUTPUT"
+run_op_support_checks "u85" "Ethos-U85" "$U85_OP_SUPPORT_OUTPUT"
 run_public_api_validator
 
 if [[ $FAILED ]]; then
diff --git a/backends/arm/test/misc/test_docgen_op_support.py b/backends/arm/test/misc/test_docgen_op_support.py
index 9f3c251478b..6c2916dd0ec 100644
--- a/backends/arm/test/misc/test_docgen_op_support.py
+++ b/backends/arm/test/misc/test_docgen_op_support.py
@@ -151,6 +151,79 @@ def test_u55_infrastructure_xfail_is_not_treated_as_unsupported() -> None:
         docgen._activate_backend(original)
 
 
+def test_u85_backend_configuration_and_profile() -> None:
+    original = docgen.ACTIVE_BACKEND_KEY
+    try:
+        config = docgen._activate_backend("u85")
+        assert config.pipeline_class_names == frozenset({"EthosU85PipelineINT"})
+        assert docgen.BACKEND_NAME == "Ethos-U85"
+        assert docgen.BACKEND_TOSA_SPEC == "TOSA-1.0+INT+int16+int4+cf"
+        assert docgen.DEFAULT_OUTPUT == Path(
+            "docs/source/backends/arm-ethos-u/U85_op_support.md"
+        )
+        assert docgen.SUPPORT_PROFILE_ORDER == ["INT"]
+
+        stmt = ast.parse("EthosU85PipelineINT(quantize=False)").body[0]
+        assert isinstance(stmt, ast.Expr)
+        call = stmt.value
+        assert isinstance(call, ast.Call)
+        # U85 is integer-only; an irrelevant quantize kwarg cannot turn it FP.
+        assert docgen._pipeline_profile(call) == "INT"
+    finally:
+        docgen._activate_backend(original)
+
+
+def test_u85_infrastructure_xfail_is_not_treated_as_unsupported() -> None:
+    original = docgen.ACTIVE_BACKEND_KEY
+    try:
+        docgen._activate_backend("u85")
+        tree = ast.parse(
+            "@common.XfailIfNoCorstone320\n" "def test_u85():\n" "    pass\n"
+        )
+        function = tree.body[0]
+        assert isinstance(function, ast.FunctionDef)
+        assert not docgen._function_is_skipped_or_xfailed(function)
+
+        semantic_tree = ast.parse(
+            "@pytest.mark.xfail(reason='unsupported')\n"
+            "def test_u85():\n"
+            "    pass\n"
+        )
+        semantic_function = semantic_tree.body[0]
+        assert isinstance(semantic_function, ast.FunctionDef)
+        assert docgen._function_is_skipped_or_xfailed(semantic_function)
+    finally:
+        docgen._activate_backend(original)
+
+
+def test_u85_explicit_coverage_attribution() -> None:
+    original = docgen.ACTIVE_BACKEND_KEY
+    try:
+        docgen._activate_backend("u85")
+        coverage = docgen._active_explicit_backend_coverage()
+
+        assert coverage[
+            (
+                "backends/arm/test/ops/test_div_tensor_mode.py",
+                "test_div_tensor_mode_u85_INT",
+            )
+        ]["INT"] == {"torch.ops.aten.div.Tensor_mode"}
+        assert coverage[("backends/arm/test/ops/test_silu.py", "test_silu_u85_INT")][
+            "INT"
+        ] == {"torch.ops.aten.silu.default"}
+    finally:
+        docgen._activate_backend(original)
+
+
+def test_non_vgf_backend_does_not_collect_vgf_custom_partition_ops() -> None:
+    original = docgen.ACTIVE_BACKEND_KEY
+    try:
+        docgen._activate_backend("u85")
+        assert docgen._collect_backend_custom_partition_ops(object()) == {}  # type: ignore[arg-type]
+    finally:
+        docgen._activate_backend(original)
+
+
 def test_backend_registry_filter_removes_unconditional_rejections(
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
diff --git a/docs/source/backends/arm-ethos-u/U85_op_support.md b/docs/source/backends/arm-ethos-u/U85_op_support.md
index 3f2c4cc25da..69e5635f168 100644
--- a/docs/source/backends/arm-ethos-u/U85_op_support.md
+++ b/docs/source/backends/arm-ethos-u/U85_op_support.md
@@ -1,136 +1,131 @@
-# EdgeIR Operator support for the U85 backend
-This list contains operators with silicon acceleration support.
-The ExecuTorch portable kernels allow running more operations with a fallback.
-8x8 designates 8-bit activation and 8-bit weight. 16x8 means 16-bit activation and 8-bit weight.
-Per-tensor and per-channel quantization are supported.
+# PyTorch operator support for the Ethos-U85 backend
 
-| EdgeIR operator | Compute DType                 | Quantization |
-| --------------- | ------------------------------| ------------ |
-| _log_softmax.default | Static integer quantization | 8x8 |
-| _softmax.default | Static integer quantization | 8x8 |
-| abs.default | Static integer quantization | 8x8 |
-| acos.default | Static integer quantization | 8x8 |
-| adaptive_avg_pool2d.default | Static integer quantization | 16x8 / 8x8 |
-| add.Tensor | Static integer quantization | 16x8 / 8x8 |
-| addmm.default | Static integer quantization | 16x8 / 8x8 |
-| alias_copy.default | Static integer quantization | 8x8 |
-| amax.default | Static integer quantization | 16x8 / 8x8 |
-| amin.default | Static integer quantization | 16x8 / 8x8 |
-| any.default | Static integer quantization | 8x8 |
-| arange.start_step | Static integer quantization | 8x8 |
-| asin.default | Static integer quantization | 8x8 |
-| asinh.default | Static integer quantization | 8x8 |
-| atan.default | Static integer quantization | 8x8 |
-| atanh.default | Static integer quantization | 8x8 |
-| avg_pool2d.default | Static integer quantization | 16x8 / 8x8 |
-| bitwise_and.Scalar | Static integer quantization | 8x8 |
-| bitwise_left_shift.Scalar | Static integer quantization | 8x8 |
-| bitwise_left_shift.Tensor | Static integer quantization | 8x8 |
-| bitwise_not.default | Static integer quantization | 8x8 |
-| bitwise_or.Scalar | Static integer quantization | 8x8 |
-| bitwise_right_shift.Scalar | Static integer quantization | 8x8 |
-| bitwise_right_shift.Tensor | Static integer quantization | 8x8 |
-| bitwise_xor.Scalar | Static integer quantization | 8x8 |
-| bmm.default | Static integer quantization | 8x8 |
-| cat.default | Static integer quantization | 16x8 / 8x8 |
-| ceil.default | Static integer quantization | 8x8 |
-| clamp.default | Static integer quantization | 16x8 / 8x8 |
-| clone.default | Static integer quantization | 8x8 |
-| conv_transpose2d.default | Static integer quantization | 8x8 |
-| convolution.default | Static integer quantization | 16x8 / 8x8 |
-| copy.default | Static integer quantization | 8x8 |
-| cos.default | Static integer quantization | 8x8 |
-| cosh.default | Static integer quantization | 8x8 |
-| cumsum.default | Static integer quantization | 8x8 |
-| div.Tensor | Static integer quantization | 8x8 |
-| div.Tensor_mode | Static integer quantization | 8x8 |
-| elu.default | Static integer quantization | 8x8 |
-| eq.Scalar | Static integer quantization | 16x8 / 8x8 |
-| erf.default | Static integer quantization | 8x8 |
-| exp.default | Static integer quantization | 8x8 |
-| expand_copy.default | Static integer quantization | 8x8 |
-| expm1.default | Static integer quantization | 8x8 |
-| eye.default | Static integer quantization | 8x8 |
-| fill.Scalar | Static integer quantization | 8x8 |
-| floor.default | Static integer quantization | 8x8 |
-| floor_divide.default | Static integer quantization | 8x8 |
-| full.default | Static integer quantization | 8x8 |
-| gather.default | Static integer quantization | 8x8 |
-| ge.Scalar | Static integer quantization | 16x8 / 8x8 |
-| ge.Tensor | Static integer quantization | 16x8 / 8x8 |
-| gelu.default | Static integer quantization | 8x8 |
-| glu.default | Static integer quantization | 8x8 |
-| gt.Scalar | Static integer quantization | 16x8 / 8x8 |
-| gt.Tensor | Static integer quantization | 16x8 / 8x8 |
-| hardsigmoid.default | Static integer quantization | 8x8 |
-| hardswish.default | Static integer quantization | 8x8 |
-| hardtanh.default | Static integer quantization | 8x8 |
-| index_put.default | Static integer quantization | 8x8 |
-| index_select.default | Static integer quantization | 8x8 |
-| le.Scalar | Static integer quantization | 16x8 / 8x8 |
-| le.Tensor | Static integer quantization | 16x8 / 8x8 |
-| leaky_relu.default | Static integer quantization | 8x8 |
-| linear.default | Static integer quantization | 16x8 / 8x8 |
-| log.default | Static integer quantization | 8x8 |
-| logical_and.default | Static integer quantization | 8x8 |
-| logical_not.default | Static integer quantization | 8x8 |
-| logical_or.default | Static integer quantization | 8x8 |
-| logical_xor.default | Static integer quantization | 8x8 |
-| logit.default | Static integer quantization | 8x8 |
-| lt.Scalar | Static integer quantization | 16x8 / 8x8 |
-| lt.Tensor | Static integer quantization | 16x8 / 8x8 |
-| masked_fill.Scalar | Static integer quantization | 8x8 |
-| maximum.default | Static integer quantization | 16x8 / 8x8 |
-| mean.dim | Static integer quantization | 8x8 |
-| minimum.default | Static integer quantization | 16x8 / 8x8 |
-| mm.default | Static integer quantization | 8x8 |
-| mul.Tensor | Static integer quantization | 16x8 / 8x8 |
-| multihead_attention.default | Static integer quantization | 8x8 |
-| native_group_norm.default | Static integer quantization | 8x8 |
-| ne.Scalar | Static integer quantization | 8x8 |
-| ne.Tensor | Static integer quantization | 8x8 |
-| neg.default | Static integer quantization | 16x8 / 8x8 |
-| ones.default | Static integer quantization | 8x8 |
-| permute_copy.default | Static integer quantization | 16x8 / 8x8 |
-| pow.Tensor_Scalar | Static integer quantization | 8x8 |
-| reciprocal.default | Static integer quantization | 8x8 |
-| relu.default | Static integer quantization | 8x8 |
-| remainder.Scalar | Static integer quantization | 8x8 |
-| remainder.Tensor | Static integer quantization | 8x8 |
-| repeat.default | Static integer quantization | 16x8 / 8x8 |
-| round.default | Static integer quantization | 8x8 |
-| rsqrt.default | Static integer quantization | 16x8 / 8x8 |
-| rsub.Scalar | Static integer quantization | 8x8 |
-| scalar_tensor.default | Static integer quantization | 8x8 |
-| sdpa.default | Static integer quantization | 8x8 |
-| select_copy.int | Static integer quantization | 8x8 |
-| select_scatter.default | Static integer quantization | 8x8 |
-| sigmoid.default | Static integer quantization | 16x8 / 8x8 |
-| sign.default | Static integer quantization | 8x8 |
-| silu.default | Static integer quantization | 8x8 |
-| sin.default | Static integer quantization | 8x8 |
-| sinh.default | Static integer quantization | 8x8 |
-| slice_copy.Tensor | Static integer quantization | 16x8 / 8x8 |
-| slice_scatter.default | Static integer quantization | 8x8 |
-| split_copy.Tensor | Static integer quantization | 8x8 |
-| split_with_sizes_copy.default | Static integer quantization | 8x8 |
-| sqrt.default | Static integer quantization | 8x8 |
-| squeeze_copy.dim | Static integer quantization | 8x8 |
-| squeeze_copy.dims | Static integer quantization | 8x8 |
-| stack.default | Static integer quantization | 8x8 |
-| sub.Tensor | Static integer quantization | 16x8 / 8x8 |
-| sum.default | Static integer quantization | 8x8 |
-| t_copy.default | Static integer quantization | 8x8 |
-| tan.default | Static integer quantization | 8x8 |
-| tanh.default | Static integer quantization | 16x8 / 8x8 |
-| transpose_copy.int | Static integer quantization | 8x8 |
-| tril.default | Static integer quantization | 16x8 / 8x8 |
-| unflatten.int | Static integer quantization | 8x8 |
-| unsqueeze_copy.default | Static integer quantization | 8x8 |
-| upsample_bilinear2d.vec | Static integer quantization | 16x8 / 8x8 |
-| var.dim | Static integer quantization | 8x8 |
-| vector_norm.default | Static integer quantization | 8x8 |
-| view_copy.default | Static integer quantization | 16x8 / 8x8 |
-| where.self | Static integer quantization | 8x8 |
-| while_loop.default | Static integer quantization | 8x8 |
-| zeros.default | Static integer quantization | 8x8 |
+<!-- DO NOT EDIT: generated by `python backends/arm/scripts/docgen/generate_op_support.py --backend u85`. -->
+
+This page lists Ethos-U85-supported PyTorch APIs and the dtype and quantization modes covered by the Ethos-U85 backend test pipeline.
+
+`8x8` means 8-bit activations and 8-bit weights. `16x8` means 16-bit activations and 8-bit weights. `8x4` means 8-bit activations and 4-bit weights.
+
+Total supported PyTorch APIs: **119**.
+
+| PyTorch API | Support profile | DType | Quantization mode |
+| --- | --- | --- | --- |
+| `torch.abs` | INT | `INT8` | 8x8 |
+| `torch.acos` | INT | `INT8` | 8x8 |
+| `torch.acosh` | INT | `INT8` | 8x8 |
+| `torch.add` / `+` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.addmm` | INT | `INT16` | 16x8 |
+| `torch.alias_copy` | INT | `INT8` | 8x8 |
+| `torch.amax` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.amin` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.any` | INT | `INT8` | 8x8 |
+| `torch.arange` | INT | `INT8` | 8x8 |
+| `torch.asin` | INT | `INT8` | 8x8 |
+| `torch.asinh` | INT | `INT8` | 8x8 |
+| `torch.atan` | INT | `INT8` | 8x8 |
+| `torch.atanh` | INT | `INT8` | 8x8 |
+| `torch.bitwise_and` / `&` | INT | `INT8` | 8x8 |
+| `torch.bitwise_left_shift` / `<<` | INT | `INT8` | 8x8 |
+| `torch.bitwise_not` / `~` | INT | `INT8` | 8x8 |
+| `torch.bitwise_or` / `\|` | INT | `INT8` | 8x8 |
+| `torch.bitwise_right_shift` / `>>` | INT | `INT8` | 8x8 |
+| `torch.bitwise_xor` / `^` | INT | `INT8` | 8x8 |
+| `torch.bmm` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.cat` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.ceil` | INT | `INT8` | 8x8 |
+| `torch.clamp` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.clone` / `torch.Tensor.clone` | INT | `INT8` | 8x8 |
+| `torch.cond` | INT | `INT8` | 8x8 |
+| `torch.conv1d` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.conv2d` | INT | `INT8`, `INT16`, `INT4` | 8x8, 8x4, 16x8 |
+| `torch.conv3d` | INT | `INT8`, `INT4` | 8x8, 8x4 |
+| `torch.conv_transpose2d` | INT | `INT8` | 8x8 |
+| `torch.cos` | INT | `INT8` | 8x8 |
+| `torch.cosh` | INT | `INT8` | 8x8 |
+| `torch.cumsum` | INT | `INT8` | 8x8 |
+| `torch.div` | INT | `INT8` | 8x8 |
+| `torch.div` / `/` | INT | `INT8` | 8x8 |
+| `torch.eq` / `==` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.erf` | INT | `INT8` | 8x8 |
+| `torch.erfinv` | INT | `INT8` | 8x8 |
+| `torch.exp` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.expm1` | INT | `INT8` | 8x8 |
+| `torch.eye` | INT | `INT8` | 8x8 |
+| `torch.fill_` | INT | `INT8` | 8x8 |
+| `torch.flip` | INT | `INT8` | 8x8 |
+| `torch.floor` | INT | `INT8` | 8x8 |
+| `torch.full` | INT | `INT8` | 8x8 |
+| `torch.full_like` | INT | `INT8` | 8x8 |
+| `torch.gather` | INT | `INT8` | 8x8 |
+| `torch.ge` / `>=` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.gt` / `>` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.index_put_` | INT | `INT8` | 8x8 |
+| `torch.index_select` | INT | `INT8` | 8x8 |
+| `torch.le` / `<=` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.log` | INT | `INT8` | 8x8 |
+| `torch.log10` | INT | `INT8` | 8x8 |
+| `torch.log_softmax` | INT | `INT8` | 8x8 |
+| `torch.logical_and` | INT | `INT8` | 8x8 |
+| `torch.logical_not` | INT | `INT8` | 8x8 |
+| `torch.logical_or` | INT | `INT8` | 8x8 |
+| `torch.logical_xor` | INT | `INT8` | 8x8 |
+| `torch.lt` / `<` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.masked_fill` / `torch.Tensor.masked_fill` | INT | `INT8` | 8x8 |
+| `torch.max_pool2d` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.maximum` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.mean` | INT | `INT8` | 8x8 |
+| `torch.minimum` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.mm` | INT | `INT8` | 8x8 |
+| `torch.mul` / `*` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.neg` / `unary -` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.nn.AvgPool2d` / `torch.nn.functional.avg_pool2d` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.nn.Conv2d` / `torch.nn.functional.conv2d` | INT | `INT8`, `INT16`, `INT4` | 8x8, 8x4, 16x8 |
+| `torch.nn.ELU` / `torch.nn.functional.elu` | INT | `INT8` | 8x8 |
+| `torch.nn.GELU` / `torch.nn.functional.gelu` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.nn.Hardsigmoid` / `torch.nn.functional.hardsigmoid` | INT | `INT8` | 8x8 |
+| `torch.nn.Hardswish` / `torch.nn.functional.hardswish` | INT | `INT8` | 8x8 |
+| `torch.nn.Hardtanh` / `torch.nn.functional.hardtanh` | INT | `INT8` | 8x8 |
+| `torch.nn.LeakyReLU` / `torch.nn.functional.leaky_relu` | INT | `INT8` | 8x8 |
+| `torch.nn.Linear` / `torch.nn.functional.linear` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.nn.SiLU` / `torch.nn.functional.silu` | INT | `INT8` | 8x8 |
+| `torch.ones` | INT | `INT8` | 8x8 |
+| `torch.permute` / `torch.Tensor.permute` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.pixel_shuffle` | INT | `INT8` | 8x8 |
+| `torch.pixel_unshuffle` | INT | `INT8` | 8x8 |
+| `torch.pow` / `**` | INT | `INT8` | 8x8 |
+| `torch.prelu` | INT | `INT8` | 8x8 |
+| `torch.reciprocal` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.relu` / `torch.nn.ReLU` | INT | `INT8` | 8x8 |
+| `torch.remainder` | INT | `INT8` | 8x8 |
+| `torch.repeat_interleave` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.round` | INT | `INT8` | 8x8 |
+| `torch.rsqrt` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.scalar_tensor` | INT | `INT8` | 8x8 |
+| `torch.select` / `torch.Tensor.select` | INT | `INT8` | 8x8 |
+| `torch.sigmoid` / `torch.nn.Sigmoid` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.sign` | INT | `INT8` | 8x8 |
+| `torch.sin` | INT | `INT8` | 8x8 |
+| `torch.sinh` | INT | `INT8` | 8x8 |
+| `torch.softmax` | INT | `INT8` | 8x8 |
+| `torch.split` / `torch.Tensor.split` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.squeeze` | INT | `INT8` | 8x8 |
+| `torch.squeeze` / `torch.Tensor.squeeze` | INT | `INT8` | 8x8 |
+| `torch.stack` | INT | `INT8` | 8x8 |
+| `torch.sub` / `-` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.sum` | INT | `INT8` | 8x8 |
+| `torch.t` / `torch.Tensor.t` | INT | `INT8` | 8x8 |
+| `torch.tan` | INT | `INT8` | 8x8 |
+| `torch.tanh` / `torch.nn.Tanh` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.Tensor.__getitem__` / `tensor slicing` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.Tensor.__setitem__` / `tensor indexing assignment` | INT | `INT8` | 8x8 |
+| `torch.Tensor.copy_` | INT | `INT8` | 8x8 |
+| `torch.Tensor.expand` | INT | `INT8` | 8x8 |
+| `torch.Tensor.repeat` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.Tensor.unfold` | INT | `INT8` | 8x8 |
+| `torch.Tensor.view` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.transpose` / `torch.Tensor.transpose` | INT | `INT8` | 8x8 |
+| `torch.unflatten` | INT | `INT8` | 8x8 |
+| `torch.unsqueeze` / `torch.Tensor.unsqueeze` | INT | `INT8` | 8x8 |
+| `torch.where` | INT | `INT8`, `INT16` | 8x8, 16x8 |
+| `torch.while_loop` | INT | `INT8` | 8x8 |
+| `torch.zeros` | INT | `INT8` | 8x8 |