diff --git a/.buildkite/test-amd.yaml b/.buildkite/test-amd.yaml
index cca01e45ba..8d2ba218be 100644
--- a/.buildkite/test-amd.yaml
+++ b/.buildkite/test-amd.yaml
@@ -516,6 +516,11 @@ steps:
   optional: true
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
+  - vllm/models/hy_v4/
+  - vllm/config/
+  - vllm/v1/worker/gpu/
+  - vllm/v1/attention/ops/
+  - vllm/v1/attention/backend.py
   - vllm/model_executor/model_loader/sharded_state_loader.py
   - vllm/model_executor/models/
   - vllm/model_executor/layers/
@@ -535,6 +540,7 @@ steps:
   - pytest models/multimodal/generation/test_phi4siglip.py -v -s -m 'distributed(num_gpus=2)'
   - VLLM_WORKER_MULTIPROC_METHOD=spawn pytest models/multimodal/generation/test_whisper.py -v -s -m 'distributed(num_gpus=2)'
   - pytest -v -s models/test_vision.py -m 'distributed(num_gpus=2)'
+  - VLLM_ROCM_USE_AITER=1 pytest -v -s models/test_hyv4_rocm.py -m 'distributed(num_gpus=2)'
 
 #--------------------------------------------------------  mi300 · benchmarks  ---------------------------------------------------------#
 
@@ -1978,9 +1984,11 @@ steps:
   - tests/models/test_terratorch.py
   - tests/models/transformers/test_backend.py
   - tests/models/test_registry.py
+  - tests/models/test_hyv4_rocm.py
   - tests/models/test_vision.py
   commands:
   - pytest -v -s models/test_terratorch.py models/transformers/test_backend.py models/test_registry.py
+  - VLLM_ROCM_USE_AITER=1 pytest -v -s models/test_hyv4_rocm.py -m 'not distributed'
   - pytest -v -s models/test_vision.py::test_simple_mrope_vision_model_spatial_merge
 
 #-----------------------------------------------------  mi300 · models / language  -----------------------------------------------------#
diff --git a/.buildkite/test_areas/models_basic.yaml b/.buildkite/test_areas/models_basic.yaml
index 93d6962868..7174612611 100644
--- a/.buildkite/test_areas/models_basic.yaml
+++ b/.buildkite/test_areas/models_basic.yaml
@@ -58,6 +58,11 @@ steps:
       timeout_in_minutes: 50
       depends_on:
       - image-build-amd
+      source_file_dependencies:
+      - tests/models/test_hyv4_rocm.py
+      commands:
+      - pytest -v -s models/test_terratorch.py models/transformers/test_backend.py models/test_registry.py
+      - VLLM_ROCM_USE_AITER=1 pytest -v -s models/test_hyv4_rocm.py -m 'not distributed'
 
 - label: ":nvidia: (B200) Inkling"
   key: inkling-unit-tests-b200
diff --git a/.buildkite/test_areas/models_distributed.yaml b/.buildkite/test_areas/models_distributed.yaml
index cf7623ce3e..f735a9b018 100644
--- a/.buildkite/test_areas/models_distributed.yaml
+++ b/.buildkite/test_areas/models_distributed.yaml
@@ -42,6 +42,13 @@ steps:
       depends_on:
       - image-build-amd
       source_file_dependencies:
+      - vllm/models/hy_v4/
+      - vllm/config/
+      - vllm/v1/worker/
+      - vllm/v1/attention/ops/
+      - vllm/v1/attention/backend.py
+      - tests/conftest.py
+      - tests/utils.py
       - vllm/model_executor/model_loader/sharded_state_loader.py
       - vllm/model_executor/models/
       - vllm/model_executor/layers/
@@ -60,8 +67,9 @@ steps:
             HIP_VISIBLE_DEVICES=0,1 pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m '(not slow_test)'
             ;;
           1)
-            pytest models/transformers/test_backend.py -v -s -m 'distributed(num_gpus=2)'
-            pytest models/language -v -s -m 'distributed(num_gpus=2)'
+            pytest models/transformers/test_backend.py -v -s -m 'distributed(num_gpus=2)' &&
+            pytest models/language -v -s -m 'distributed(num_gpus=2)' &&
+            VLLM_ROCM_USE_AITER=1 pytest -v -s models/test_hyv4_rocm.py -m 'distributed(num_gpus=2)'
             ;;
           2)
             pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_phi4siglip.py
diff --git a/tests/models/test_hyv4_rocm.py b/tests/models/test_hyv4_rocm.py
new file mode 100644
index 0000000000..b6dc8d7042
--- /dev/null
+++ b/tests/models/test_hyv4_rocm.py
@@ -0,0 +1,137 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import math
+
+import pytest
+
+from tests.utils import multi_gpu_marks
+from vllm import SamplingParams
+from vllm.config import CompilationConfig
+from vllm.config.compilation import CompilationMode, CUDAGraphMode
+from vllm.platforms import current_platform
+from vllm.v1.metrics.reader import Counter
+
+pytestmark = pytest.mark.skipif(
+    not current_platform.is_rocm(), reason="ROCm-specific tests"
+)
+
+
+def _small_hyv4_config(config):
+    # Apply to both target and MTP draft while retaining MLA/indexer dimensions.
+    config.update(
+        {
+            "hidden_size": 512,
+            "num_hidden_layers": 2,
+            "num_attention_heads": 64,
+            "q_lora_rank": 128,
+            "intermediate_size": 512,
+            "moe_intermediate_size": 256,
+            "n_routed_experts": 4,
+            "num_experts_per_tok": 2,
+            "n_shared_experts": 1,
+            "enable_ihc": True,
+            "index_n_heads": 32,
+            "index_topk": 2048,
+            "layer_types": ["deepseek_sparse_attention"] * 2,
+            "indexer_types": ["full", "shared"],
+            "num_nextn_predict_layers": 1,
+            "vocab_size": 256,
+            "bos_token_id": 1,
+            "eos_token_id": 2,
+            "pad_token_id": 0,
+        }
+    )
+    return config
+
+
+def _num_captured_graphs(_worker):
+    from vllm.compilation.counter import compilation_counter
+
+    return compilation_counter.num_cudagraph_captured
+
+
+@pytest.mark.parametrize(
+    "tp,enforce_eager,mtp,dtype,kv_cache_dtype",
+    [
+        pytest.param(1, True, False, "bfloat16", "auto", id="eager-tp1"),
+        pytest.param(1, True, False, "float16", "auto", id="eager-fp16"),
+        pytest.param(1, True, False, "bfloat16", "fp8", id="eager-fp8-kv"),
+        pytest.param(
+            2,
+            False,
+            False,
+            "bfloat16",
+            "auto",
+            id="graphs-tp2",
+            marks=multi_gpu_marks(num_gpus=2),
+        ),
+        pytest.param(1, True, True, "bfloat16", "auto", id="eager-mtp"),
+    ],
+)
+def test_hyv4_dummy_generation(
+    vllm_runner,
+    enable_pickle,
+    tp: int,
+    enforce_eager: bool,
+    mtp: bool,
+    dtype: str,
+    kv_cache_dtype: str,
+) -> None:
+    """Exercise prefill, decode, and batch consistency with dummy HY weights."""
+    with vllm_runner(
+        "tencent/Hy4-preview",
+        trust_remote_code=True,
+        skip_tokenizer_init=True,
+        load_format="dummy",
+        disable_log_stats=not mtp,
+        dtype=dtype,
+        kv_cache_dtype=kv_cache_dtype,
+        hf_overrides=_small_hyv4_config,
+        max_model_len=256,
+        max_num_batched_tokens=128,
+        max_num_seqs=8,
+        enable_chunked_prefill=True,
+        enable_prefix_caching=False,
+        kv_cache_memory_bytes=128 * 1024 * 1024,
+        enforce_eager=enforce_eager,
+        tensor_parallel_size=tp,
+        speculative_config={"method": "mtp", "num_speculative_tokens": 2}
+        if mtp
+        else None,
+        seed=17,
+        # Exercise supported decode graphs independently of default graph policy.
+        compilation_config=CompilationConfig(
+            mode=CompilationMode.NONE,
+            cudagraph_mode=CUDAGraphMode.NONE
+            if enforce_eager
+            else CUDAGraphMode.FULL_DECODE_ONLY,
+            cudagraph_capture_sizes=[] if enforce_eager else [1, 2, 4],
+        ),
+    ) as model:
+        if not enforce_eager:
+            assert model.collective_rpc(_num_captured_graphs) == [3] * tp
+        prompts = [
+            {"prompt_token_ids": [11, 12, 13, 14]},
+            {"prompt_token_ids": list(range(20, 84))},
+        ]
+        params = SamplingParams(
+            temperature=0, max_tokens=4, ignore_eos=True, logprobs=1
+        )
+        outputs = model.llm.generate(prompts, params)
+        assert len(outputs) == len(prompts)
+        for prompt, output in zip(prompts, outputs):
+            completion = output.outputs[0]
+            assert len(completion.token_ids) == 4
+            assert completion.cumulative_logprob is not None
+            assert math.isfinite(completion.cumulative_logprob)
+            single = model.llm.generate([prompt], params)[0].outputs[0]
+            assert single.token_ids == completion.token_ids
+
+        if mtp:
+            assert any(
+                isinstance(metric, Counter)
+                and metric.name == "vllm:spec_decode_num_drafts"
+                and metric.value > 0
+                for metric in model.llm.get_metrics()
+            ), "MTP drafter did not run"