diff --git a/mlx_vlm/models/qwen3_5/language.py b/mlx_vlm/models/qwen3_5/language.py
index 74f672984..061477ec1 100644
--- a/mlx_vlm/models/qwen3_5/language.py
+++ b/mlx_vlm/models/qwen3_5/language.py
@@ -29,11 +29,13 @@ def __init__(
         max_position_embeddings=2048,
         base=10000,
         mrope_section=[11, 11, 0],
+        rope_parameters=None,
     ):
         super().__init__(
             dim,
             max_position_embeddings=max_position_embeddings,
             base=base,
+            rope_parameters=rope_parameters,
             mrope_section=mrope_section,
             style="interleaved",
         )
@@ -258,11 +260,7 @@ def _target_verify_qlinear_header(bits: int, group_size: int) -> str:
       }
       return scale * accum + sum * bias;
     }
-""".replace(
-        "__BITS__", str(bits)
-    ).replace(
-        "__GS__", str(group_size)
-    )
+""".replace("__BITS__", str(bits)).replace("__GS__", str(group_size))
 
 
 _TARGET_VERIFY_QMV_SOURCE = r"""
@@ -1391,6 +1389,7 @@ def __init__(self, args: TextConfig):
             max_position_embeddings=args.max_position_embeddings,
             base=args.rope_parameters["rope_theta"],
             mrope_section=args.rope_parameters["mrope_section"],
+            rope_parameters=args.rope_parameters,
         )
 
     def __call__(
diff --git a/mlx_vlm/models/rope_utils.py b/mlx_vlm/models/rope_utils.py
index 6fb292ae6..af7cbee73 100644
--- a/mlx_vlm/models/rope_utils.py
+++ b/mlx_vlm/models/rope_utils.py
@@ -1,3 +1,4 @@
+import math
 from functools import lru_cache
 from typing import Optional, Sequence
 
@@ -397,6 +398,41 @@ def compute_inv_freq(dim: int, base: float):
     return 1.0 / (base ** (mx.arange(0, dim, 2).astype(mx.float32) / dim))
 
 
+def apply_cope_clip(
+    inv_freq,
+    original_max_position_embeddings: Optional[int] = None,
+    clip_n: Optional[int] = None,
+):
+    """Soft-clip out-of-distribution low frequencies (CoPE, arXiv:2602.05258).
+
+    Frequency components whose rotation period exceeds the pre-training
+    context window never complete a full rotation during training and go
+    out-of-distribution when extrapolating past it. CoPE attenuates them
+    with a raised-cosine (Hann) taper: the boundary component is left
+    untouched and the lowest-frequency component is frozen (inv_freq=0),
+    avoiding the spectral leakage of a hard cutoff.
+
+    When ``clip_n`` is not given it is derived from
+    ``original_max_position_embeddings``: every component with period
+    ``2*pi/inv_freq`` greater than the window is clipped.
+    """
+    n = inv_freq.shape[0]
+    if clip_n is None:
+        if original_max_position_embeddings is None:
+            raise ValueError(
+                "CoPE requires either clip_n or "
+                "original_max_position_embeddings to size the clip."
+            )
+        periods = 2 * math.pi / inv_freq
+        clip_n = int((periods > original_max_position_embeddings).sum())
+    clip_n = min(int(clip_n), n)
+    if clip_n == 0:
+        return inv_freq
+    theta = mx.linspace(0, math.pi, num=clip_n)
+    mask = 0.5 * (1.0 + mx.cos(theta))
+    return mx.concatenate([inv_freq[: n - clip_n], inv_freq[n - clip_n :] * mask])
+
+
 @mx.compile
 def _apply_selected_mrope_frequency_layout(freqs, position_selector):
     indices = mx.broadcast_to(
@@ -535,6 +571,15 @@ def __init__(
         self.base = base
         self.style = style
         self._inv_freq = compute_inv_freq(dim, base)
+        rope_params = rope_parameters or rope_scaling or {}
+        if (rope_params.get("rope_type") or rope_params.get("type")) == "cope":
+            self._inv_freq = apply_cope_clip(
+                self._inv_freq,
+                rope_params.get(
+                    "original_max_position_embeddings", max_position_embeddings
+                ),
+                rope_params.get("clip_n"),
+            )
         self.attention_scaling = attention_scaling
         self.cast_output = cast_output
         self._mrope_section = list(
diff --git a/mlx_vlm/tests/test_cope_rope.py b/mlx_vlm/tests/test_cope_rope.py
new file mode 100644
index 000000000..2a2780ad7
--- /dev/null
+++ b/mlx_vlm/tests/test_cope_rope.py
@@ -0,0 +1,104 @@
+"""Tests for CoPE (Clipped RoPE) soft-clipping in rope_utils.
+
+CoPE: Clipped RoPE as A Scalable Free Lunch for Long Context LLMs
+(arXiv:2602.05258).
+"""
+
+import math
+
+import mlx.core as mx
+import pytest
+
+from mlx_vlm.models.rope_utils import (
+    MRoPERotaryEmbedding,
+    apply_cope_clip,
+    compute_inv_freq,
+)
+
+# Qwen3.5/3.6-family rope geometry: theta=10M, 64 rotary dims, native 262144.
+DIM, BASE, NATIVE = 64, 10_000_000, 262_144
+
+
+def test_auto_clip_sizing():
+    inv_freq = compute_inv_freq(DIM, BASE)
+    clipped = apply_cope_clip(inv_freq, original_max_position_embeddings=NATIVE)
+
+    # Components with period 2*pi/inv_freq > 262144: i >= 22, i.e. 10 of 32.
+    periods = 2 * math.pi / inv_freq
+    expected_n = int((periods > NATIVE).sum())
+    assert expected_n == 10
+
+    # Unclipped head is bit-identical; boundary component preserved (mask=1).
+    assert mx.allclose(clipped[:22], inv_freq[:22])
+    assert mx.allclose(clipped[22], inv_freq[22], rtol=1e-5)
+    # Lowest-frequency component is frozen entirely.
+    assert clipped[-1] == 0.0
+    # Taper is monotone non-increasing across the clipped range.
+    tail = clipped[22:]
+    assert mx.all(tail[:-1] >= tail[1:])
+
+
+def test_explicit_clip_n_and_noop():
+    inv_freq = compute_inv_freq(DIM, BASE)
+
+    clipped = apply_cope_clip(inv_freq, clip_n=4)
+    assert mx.allclose(clipped[:28], inv_freq[:28])
+    assert clipped[-1] == 0.0
+
+    # clip_n=0 is a no-op.
+    assert mx.allclose(apply_cope_clip(inv_freq, clip_n=0), inv_freq)
+
+    # clip_n is bounded by the number of components.
+    clipped = apply_cope_clip(inv_freq, clip_n=999)
+    assert clipped.shape == inv_freq.shape
+
+
+def test_requires_sizing_information():
+    inv_freq = compute_inv_freq(DIM, BASE)
+    with pytest.raises(ValueError):
+        apply_cope_clip(inv_freq)
+
+
+def test_mrope_embedding_integration():
+    rope = MRoPERotaryEmbedding(
+        DIM,
+        max_position_embeddings=NATIVE,
+        base=BASE,
+        rope_parameters={
+            "rope_type": "cope",
+            "original_max_position_embeddings": NATIVE,
+            "mrope_section": [11, 11, 10],
+        },
+    )
+    raw = compute_inv_freq(DIM, BASE)
+    assert rope.inv_freq[-1] == 0.0
+    assert mx.allclose(rope.inv_freq[:22], raw[:22])
+
+    # Without rope_type=cope the frequencies are untouched.
+    rope = MRoPERotaryEmbedding(
+        DIM,
+        max_position_embeddings=NATIVE,
+        base=BASE,
+        rope_parameters={"mrope_section": [11, 11, 10]},
+    )
+    assert mx.allclose(rope.inv_freq, raw)
+
+
+def test_qwen3_5_rotary_embedding_passthrough():
+    from mlx_vlm.models.qwen3_5.language import Qwen3_5RotaryEmbedding
+
+    rope = Qwen3_5RotaryEmbedding(
+        DIM,
+        max_position_embeddings=NATIVE,
+        base=BASE,
+        mrope_section=[11, 11, 10],
+        rope_parameters={
+            "rope_type": "cope",
+            "original_max_position_embeddings": NATIVE,
+            "rope_theta": BASE,
+            "partial_rotary_factor": 0.25,
+            "mrope_section": [11, 11, 10],
+        },
+    )
+    assert rope.inv_freq[-1] == 0.0
+    assert rope.inv_freq.shape[0] == DIM // 2