diff --git a/tests/kernels/utils/fp4_utils.py b/tests/kernels/utils/fp4_utils.py
index c02a694a2..90ec47811 100644
--- a/tests/kernels/utils/fp4_utils.py
+++ b/tests/kernels/utils/fp4_utils.py
@@ -60,6 +60,63 @@ def f32_to_e8m0(x):
     return exponent.view(fp8_e8m0)
 
 
+def f32_to_e8m0_even(amax: Tensor, *, emax: int, mbits: int) -> Tensor:
+    """OCP MX v1.0 §6.3 ``even_round`` E8M0 scale assignment.
+
+    Given a per-block ``amax = max |x_i|`` (non-negative float32), returns the
+    E8M0 byte (uint8) that encodes the per-block scale
+    ``X_scale = 2^(floor(log2(amax_rounded)) - emax)``, where
+    ``amax_rounded`` is ``amax`` rounded to ``mbits``-of-mantissa precision via
+    round-half-to-even (i.e. add half-ULP at f32 mantissa bit
+    ``23 - mbits - 1`` and mask off the mantissa).
+
+    Args:
+        amax: float32 tensor of per-block absolute maxima. Must be
+            non-negative; NaN entries propagate to 0xFF.
+        emax: largest representable element-format exponent. For E2M1 use 2,
+            E2M3 use 2, E3M2 use 4, E4M3 use 8, etc. (= 2^(ebits-1) for
+            symmetric exponent-bias formats).
+        mbits: element-format mantissa width in bits. Used only to size the
+            half-ULP added to ``amax`` before truncation; controls
+            tie-breaking. E2M1: 1, E2M3: 3, E3M2: 2, E4M3: 3.
+
+    Returns:
+        uint8 tensor (viewed as fp8_e8m0 when supported) of the same shape as
+        ``amax`` holding the E8M0 codepoint ``k + 127`` where
+        ``k = floor(log2(amax_rounded)) - emax``.
+
+    Notes:
+        ``f32_to_e8m0`` above expects pre-divided input ``amax / max_normal``
+        and is biased one exponent step low on ~68% of blocks vs. the OCP
+        spec when ``max_normal != 2^emax`` (e.g. E2M3 max_normal = 7.5, so
+        ``1/max_normal`` lies in (0.5, 1) of a binade, dragging the rounded
+        exponent down by one). Use this function instead when producing
+        scales that need to interoperate with Quark / OCP-spec checkpoints.
+        See ``quark.torch.quantization.utils.even_round`` for the reference
+        implementation this matches bit-for-bit.
+    """
+    assert amax.dtype == torch.float32, f"amax must be float32, got {amax.dtype}"
+    amax = amax.contiguous()
+    amax_i32 = amax.view(torch.int32)
+    # Half-ULP at mantissa bit (23 - mbits - 1). On uint32 add this would
+    # carry cleanly into the exponent; we go through int64 because HIP
+    # doesn't implement uint32 ops.
+    val_to_add = 1 << (23 - mbits - 1)
+    sign_exp_mask = 0x7F800000  # sign bit is 0 since amax >= 0
+    rounded = ((amax_i32.to(torch.int64) & 0xFFFFFFFF) + val_to_add) & sign_exp_mask
+    # rounded_exp = f32 exponent field of amax_rounded = floor(log2(.)) + 127
+    rounded_exp = (rounded >> 23) & 0xFF
+    # E8M0 byte = (rounded_exp - 127) - emax + 127 = rounded_exp - emax
+    byte = (rounded_exp - emax).clamp_(min=0, max=254)
+    # Edge cases (per Quark): zero amax → smallest normal scale (byte=1);
+    # NaN amax → 0xFF.
+    nan_mask = ((amax_i32.to(torch.int64) >> 23) & 0xFF) == 0xFF
+    zero_mask = amax == 0
+    byte = torch.where(zero_mask, torch.full_like(byte, 1), byte)
+    byte = torch.where(nan_mask, torch.full_like(byte, 0xFF), byte)
+    return byte.to(torch.uint8).view(fp8_e8m0)
+
+
 def e8m0_to_f32(scale_e8m0_biased):
     scale_e8m0_biased = scale_e8m0_biased.view(torch.uint8)
     zero_case = scale_e8m0_biased == 0
diff --git a/tests/kernels/utils/test_fp4_utils.py b/tests/kernels/utils/test_fp4_utils.py
new file mode 100644
index 000000000..61547740d
--- /dev/null
+++ b/tests/kernels/utils/test_fp4_utils.py
@@ -0,0 +1,157 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: MIT
+# Copyright (C) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
+
+"""Unit tests for ``tests.kernels.utils.fp4_utils``.
+
+Today these are CPU-only (no MFMA exercised). The most important coverage
+is ``f32_to_e8m0_even`` vs. the legacy ``f32_to_e8m0(amax / max_normal)``
+path: the two recipes diverge by one E8M0 step on the majority of inputs
+when ``max_normal`` is not exactly ``2^emax`` (i.e. for E2M3/E3M2/E4M3).
+"""
+
+from __future__ import annotations
+
+import math
+import os
+import sys
+
+import pytest
+import torch
+
+_REPO_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
+if _REPO_ROOT not in sys.path:
+    sys.path.insert(0, _REPO_ROOT)
+
+from tests.kernels.utils import fp4_utils  # noqa: E402
+
+# (dtype_name, emax, mbits, max_normal) -- straight from the OCP MX v1.0 spec.
+_OCP_MX_TYPES = [
+    ("E2M1", 2, 1, 6.0),  # MXFP4   max = 4 * 1.5
+    ("E2M3", 2, 3, 7.5),  # MXFP6   max = 4 * 1.875
+    ("E3M2", 4, 2, 28.0),  # MXFP6   max = 16 * 1.75
+    ("E4M3", 8, 3, 448.0),  # MXFP8   max = 256 * 1.75
+    ("E5M2", 15, 2, 57344.0),
+]
+
+
+def _e8m0_to_f32(byte_u8: torch.Tensor) -> torch.Tensor:
+    """uint8 E8M0 -> float32, OCP convention. byte=0 reserved (0+), byte=255 NaN."""
+    bits = byte_u8.to(torch.int64) << 23
+    f = bits.to(torch.int32).view(torch.float32)
+    f = torch.where(byte_u8 == 0, torch.full_like(f, 2.0**-126), f)
+    f = torch.where(byte_u8 == 0xFF, torch.full_like(f, float("nan")), f)
+    return f
+
+
+def _reference_even_round_byte(amax: float, emax: int, mbits: int) -> int:
+    """Single-element reference: log2-floor-with-half-ULP-round-to-even.
+
+    Independent re-derivation of the OCP §6.3 formula in plain python; used
+    to cross-check the vectorized ``f32_to_e8m0_even`` against arithmetic
+    that doesn't share its bit-manipulation tricks.
+    """
+    if amax == 0.0:
+        return 1  # smallest normal scale, matches Quark even_round
+    if math.isnan(amax):
+        return 0xFF
+    # Add half-ULP at f32 mantissa bit (23 - mbits - 1), mask off mantissa.
+    import struct
+
+    bits = struct.unpack("<I", struct.pack("<f", amax))[0]
+    bits = (bits + (1 << (23 - mbits - 1))) & 0x7F800000
+    rounded = struct.unpack("<f", struct.pack("<I", bits))[0]
+    if rounded == 0.0:
+        return 0
+    k = int(math.floor(math.log2(rounded))) - emax
+    return max(0, min(254, k + 127))
+
+
+@pytest.mark.parametrize("dtype_name,emax,mbits,max_normal", _OCP_MX_TYPES)
+def test_f32_to_e8m0_even_matches_python_reference(dtype_name, emax, mbits, max_normal):
+    """Vectorized impl matches the per-element python reference bit-for-bit."""
+    g = torch.Generator(device="cpu").manual_seed(0)
+    # Sample amax across many binades + a few exact powers of 2 (tie points).
+    amax = torch.cat(
+        [
+            torch.rand(2048, generator=g, dtype=torch.float32) * 8.0,
+            torch.rand(2048, generator=g, dtype=torch.float32) * max_normal * 4,
+            # exact powers of 2 — tie points where rounding mode matters
+            torch.tensor([2.0**k for k in range(-10, 12)], dtype=torch.float32),
+            torch.tensor([0.0, max_normal, max_normal * 0.5], dtype=torch.float32),
+        ]
+    )
+    got = fp4_utils.f32_to_e8m0_even(amax, emax=emax, mbits=mbits).view(torch.uint8)
+    want = torch.tensor(
+        [_reference_even_round_byte(a.item(), emax, mbits) for a in amax],
+        dtype=torch.uint8,
+    )
+    mism = (got.int() - want.int() != 0).sum().item()
+    assert mism == 0, (
+        f"{dtype_name}: {mism}/{amax.numel()} byte mismatches vs python reference\n"
+        f"first 10 amax / got / want:\n"
+        + "\n".join(
+            f"  amax={a.item():.6g}  got={g.item():3d}  want={w.item():3d}"
+            for a, g, w in zip(amax[:10], got[:10], want[:10])
+        )
+    )
+
+
+@pytest.mark.parametrize("dtype_name,emax,mbits,max_normal", _OCP_MX_TYPES)
+def test_e8m0_even_scale_within_one_binade_of_optimal(dtype_name, emax, mbits, max_normal):
+    """OCP §6.3 ``even_round`` rounds ``log2(amax)`` round-to-nearest-even,
+    so the decoded scale ``S = 2^k`` is within one binade of the optimal
+    ``amax / max_normal``: ``0.5 <= S / (amax / max_normal) <= 2.0`` modulo
+    the ``(1 + max_mant)`` factor of ``max_normal``. Equivalently
+    ``S * max_normal`` falls in ``[amax / 2, 2 * amax]``.
+
+    This is the right invariant for spec-compliant even_round — the
+    stronger "S * max_normal >= amax" (no saturation) is NOT guaranteed
+    by RTNE because round-down can win at tie points. The earlier
+    ``f32_to_e8m0(amax / max_normal)`` path biases low by roughly one step
+    on most inputs and would fail the upper bound for many blocks.
+    """
+    g = torch.Generator(device="cpu").manual_seed(1)
+    amax = torch.rand(4096, generator=g, dtype=torch.float32) * max_normal * 3 + 1e-6
+    byte = fp4_utils.f32_to_e8m0_even(amax, emax=emax, mbits=mbits).view(torch.uint8)
+    scale = _e8m0_to_f32(byte)
+    ratio = (scale * max_normal) / amax
+    # Round-to-nearest in log2 space ⇒ ratio in [1/(1+max_mant_frac), 2*max_mant_frac].
+    # Tight numerical bound is 0.5 < ratio < 2; the tie may land exactly at
+    # the edges, so use a small slack.
+    n_lo = (ratio < 0.5 - 1e-5).sum().item()
+    n_hi = (ratio > 2.0 + 1e-5).sum().item()
+    assert n_lo == 0 and n_hi == 0, (
+        f"{dtype_name}: even_round produced scale outside [0.5, 2.0] of "
+        f"amax/max_normal: {n_lo} below, {n_hi} above. "
+        f"Range observed: [{ratio.min().item():.4g}, {ratio.max().item():.4g}]"
+    )
+
+
+def test_f32_to_e8m0_legacy_off_by_one_on_e2m3():
+    """Document the existing ``f32_to_e8m0(amax / max_normal)`` bias.
+
+    The legacy path is consistently one E8M0 step low for ~60-70% of random
+    amax inputs in E2M3 because 1/7.5 lies in (0.5, 1) of a binade. This
+    test fails-loudly only if the legacy function's behavior changes; the
+    intent is to pin down *why* ``f32_to_e8m0_even`` exists.
+    """
+    emax, mbits, max_normal = 2, 3, 7.5
+    g = torch.Generator(device="cpu").manual_seed(2)
+    amax = torch.rand(4096, generator=g, dtype=torch.float32) * max_normal
+    even = fp4_utils.f32_to_e8m0_even(amax, emax=emax, mbits=mbits).view(torch.uint8)
+    legacy = fp4_utils.f32_to_e8m0((amax / max_normal).clamp_(min=2**-126))
+    legacy = legacy.view(torch.uint8)
+    diff = even.int() - legacy.int()
+    # Every diverging byte should be even == legacy + 1 (legacy is biased low).
+    bad_dirs = ((diff != 0) & (diff != 1)).sum().item()
+    assert bad_dirs == 0, (
+        f"Unexpected disagreement direction: {bad_dirs} bytes diverged in "
+        f"directions other than +1. Distribution: {torch.unique(diff, return_counts=True)}"
+    )
+    n_mism = (diff != 0).sum().item()
+    # Loose lower bound: on uniform amax in [0, max_normal] we see ~60%+.
+    assert n_mism > amax.numel() // 3, (
+        f"Expected ≥1/3 of bytes to disagree (legacy off-by-one on E2M3); "
+        f"got {n_mism}/{amax.numel()}. Has f32_to_e8m0 been changed?"
+    )