diff --git a/tests/models/language/generation/test_hybrid.py b/tests/models/language/generation/test_hybrid.py
index c3e6d7899e2e..2724f612cee0 100644
--- a/tests/models/language/generation/test_hybrid.py
+++ b/tests/models/language/generation/test_hybrid.py
@@ -8,6 +8,7 @@
 from tests.models.registry import HF_EXAMPLE_MODELS
 from tests.utils import multi_gpu_test
 from vllm.engine.arg_utils import EngineArgs
+from vllm.platforms import current_platform
 from vllm.sampling_params import SamplingParams
 from vllm.v1.cudagraph_dispatcher import CudagraphDispatcher
 
@@ -577,6 +578,10 @@ def test_apc_multiple_prompts_all_cached_outputs(
         model, max_model_len, tensor_parallel_size=tensor_parallel_size
     )
     vllm_runner_kwargs["mamba_ssm_cache_dtype"] = "float32"
+    # Reduce the effects of batch variance on ROCm since batch invariance is not
+    # yet supported. See: https://github.com/vllm-project/vllm/issues/27433
+    if current_platform.is_rocm():
+        vllm_runner_kwargs["max_num_seqs"] = 4
 
     vllm_outputs_no_cache, _ = _get_vLLM_output(
         vllm_runner, vllm_runner_kwargs, generated_prompts, max_tokens, num_logprobs
diff --git a/vllm/model_executor/layers/mamba/mamba_mixer.py b/vllm/model_executor/layers/mamba/mamba_mixer.py
index 134e1dfd6283..adc643c385e1 100644
--- a/vllm/model_executor/layers/mamba/mamba_mixer.py
+++ b/vllm/model_executor/layers/mamba/mamba_mixer.py
@@ -214,6 +214,12 @@ def _ssm_transform(
             time_step = self.dt_layernorm(time_step.contiguous())
             B = self.b_layernorm(B.contiguous())
             C = self.c_layernorm(C.contiguous())
+
+        # ROCm: tensor from split is non-contiguous, causing incorrect
+        # GEMM results in dt_proj.
+        if current_platform.is_rocm():
+            time_step = time_step.contiguous()
+
         discrete_time_step = self.dt_proj(time_step)[0].transpose(-2, -1)
         return discrete_time_step, B, C